Conventional echocardiography can sometimes pose a challenge to diagnosis due to sub-optimal images.Ultrasound contrast agents(UCAs)have been shown to drastically enhance imaging quality,particularly depicting the lef...Conventional echocardiography can sometimes pose a challenge to diagnosis due to sub-optimal images.Ultrasound contrast agents(UCAs)have been shown to drastically enhance imaging quality,particularly depicting the left ventricular endocardial borders.Their use during echocardiography has become a valuable tool in non-invasive diagnostics.UCAs provide higher-quality images that may ultimately reduce the length of hospital stays and improve patient care.The higher cost associated with UCAs in many situations has been an impediment to frequent use.However,when used as an initial diagnostic test,UCA during rest echocardiogram is more cost-effective than the traditional diagnostic approach,which frequently includes multiple tests and imaging studies to make an accurate diagnosis.They can be easily performed across multiple patient settings and provide optimal images that allow clinicians to make sound medical decisions.This consequently allows for better diagnostic accuracies and improvement in patient care.展开更多
Spectral computed tomography(CT)imaging as an advanced and non-invasive technique is of importance in the diagnosis of disease.Therefore,it is significant to develop safe and high-performance contrast agents for spect...Spectral computed tomography(CT)imaging as an advanced and non-invasive technique is of importance in the diagnosis of disease.Therefore,it is significant to develop safe and high-performance contrast agents for spectral CT imaging.Herein,we synthesized a small-molecule erbium chelate(ErDOTA dimeglumine),with the advantages of favorable colloidal and structure stability,good biocompatibility and biosafety,and sensitive spectral CT imaging ability in vitro and in vivo.Erbium chelate exhibits strong X-ray attenuation capability and the energy-dependent attenuation in the range of 40-160 keV due to the high K-edge value of Er(57.5 keV).Especially,the slope of the Hounsfield unit(HU)curve for erbium chelate is 1.5 times that of iohexol at 50 keV,and 5.6 times that of iohexol at130 keV.We then applied erbium chelate in the in vivo spectral CT imaging of healthy mice and DSSinduced colitis mice.It is found that erbium chelate is rapidly metabolized from the intestinal tract in healthy mice within 12 h due to favorable biocompatibility,while it is enriched and displays brighter signals in the inflammatory site of colon in colitis mice.Specifically,the CT value in the large intestines of colitis mice 12 h after erbium chelate administration is 53.0,which is much higher than that of healthy mice(8.3),showing great potential for sensitive and accurate diagnosis of inflammatory bowel disease.Moreover,compared with the clinically used contrast agent iohexol,erbium chelate shows better spectral CT imaging performance in both healthy and colitis mice at low to high energy settings.Superior CT imaging is also observed in CT26 tumor-bearing mice after administration with erbium chelate in comparison to iohexol.In summary,the small-molecule erbium chelate is expected to be a safe and highperfo rmance co ntrast agent for spectral CT imaging to promote the diagnosis of gastrointestinal diseases.展开更多
Ultrasmall superparamagnetic iron oxide nanoparticles(usSPIONs)are promising alternatives to gadolinium‐based contrast agents for positive contrast enhancement in magnetic resonance imaging(MRI).Unlike larger SPIONs ...Ultrasmall superparamagnetic iron oxide nanoparticles(usSPIONs)are promising alternatives to gadolinium‐based contrast agents for positive contrast enhancement in magnetic resonance imaging(MRI).Unlike larger SPIONs that primarily function as T2/T2*negative contrast agents,usSPIONs with core diameters below 5 nm can effectively shorten T1 relaxation times,producing bright signals in T1‐weighted images.This distinct behavior stems from their unique magnetic properties,including single‐domain configurations,surface spin canting,and rapid Néel relaxation dynamics,which are particularly enhanced at low magnetic field strengths.The biocompatibility of iron oxide,efficient renal clearance pathways,and versatility for surface functionalization offer potential advantages over gadolinium‐based agents,especially regarding safety concerns related to nephrogenic systemic fibrosis and gadolinium deposition.These nanoparticles show particular promise for applications in lowfield MRI,vascular imaging,targeted molecular imaging,and theranostic platforms.Although challenges remain in optimizing synthesis methods for consistent production of monodisperse usSPIONs with tailored surface chemistry,ongoing research continues to advance their potential for clinical translation.This review explores the mechanisms,synthesis approaches,applications,and future perspectives of usSPIONs as positive contrast agents in MRI.展开更多
The syntheses of Gd(OH)_(3)and Gd(OH)_(3)-based nanomaterials have been reported and these materials have been developed as excellent MRI contrast agents.Due to the close interrelation between their morphology and pro...The syntheses of Gd(OH)_(3)and Gd(OH)_(3)-based nanomaterials have been reported and these materials have been developed as excellent MRI contrast agents.Due to the close interrelation between their morphology and properties,it has resulted in the development of various particle sizes and shapes of Gd(OH)_(3)and Gd(OH)_(3)-based nanomaterials.This has led to the extension of the uses of the materials to photocatalysis,drug delivery,and CT image contrast agents.Accordingly,these applications have been compiled and discussed in depth in this review.The potential of these materials in the above applications has started to attract significant attention.Moreover,the compilation of in-vitro toxicity studies from the literature was also discussed to facilitate the biocompatibility of the developed Gd(OH)_(3)nanomaterials.However,despite the rapid progress of Gd(OH)_(3)and Gd(OH)_(3)-based nanomaterials,there are still knowledge gaps in certain areas.Therefore,this review provides insights into the recent development of Gd(OH)_(3)and Gd(OH)_(3)-based nanomaterials to aid in accelerating novel developments.展开更多
AI Agent技术凭借环境感知、自主决策与协同执行能力,为财务共享服务中心的智能化升级提供了新型技术方案。财务共享中心作为集约化财务管理载体,在业务规模扩张与数据量激增的背景下,面临着风险识别滞后与资金结算效率不足等挑战,AI Ag...AI Agent技术凭借环境感知、自主决策与协同执行能力,为财务共享服务中心的智能化升级提供了新型技术方案。财务共享中心作为集约化财务管理载体,在业务规模扩张与数据量激增的背景下,面临着风险识别滞后与资金结算效率不足等挑战,AI Agent通过构建智能识别预警系统、动态评估管控体系、自动化应急处置机制及全程追踪管理框架,实现了交易异常、信用风险、资金异常与合规风险的精准防控。展开更多
Artificial intelligence(AI)is reshaping financial systems and services,as intelligent AI agents increasingly form the foundation of autonomous,goal-driven systems capable of reasoning,learning,and action.This review s...Artificial intelligence(AI)is reshaping financial systems and services,as intelligent AI agents increasingly form the foundation of autonomous,goal-driven systems capable of reasoning,learning,and action.This review synthesizes recent research and developments in the application of AI agents across core financial domains.Specifically,it covers the deployment of agent-based AI in algorithmic trading,fraud detection,credit risk assessment,roboadvisory,and regulatory compliance(RegTech).The review focuses on advanced agent-based methodologies,including reinforcement learning,multi-agent systems,and autonomous decision-making frameworks,particularly those leveraging large language models(LLMs),contrasting these with traditional AI or purely statistical models.Our primary goals are to consolidate current knowledge,identify significant trends and architectural approaches,review the practical efficiency and impact of current applications,and delineate key challenges and promising future research directions.The increasing sophistication of AI agents offers unprecedented opportunities for innovation in finance,yet presents complex technical,ethical,and regulatory challenges that demand careful consideration and proactive strategies.This review aims to provide a comprehensive understanding of this rapidly evolving landscape,highlighting the role of agent-based AI in the ongoing transformation of the financial industry,and is intended to serve financial institutions,regulators,investors,analysts,researchers,and other key stakeholders in the financial ecosystem.展开更多
To address the issue of scarce labeled samples and operational condition variations that degrade the accuracy of fault diagnosis models in variable-condition gearbox fault diagnosis,this paper proposes a semi-supervis...To address the issue of scarce labeled samples and operational condition variations that degrade the accuracy of fault diagnosis models in variable-condition gearbox fault diagnosis,this paper proposes a semi-supervised masked contrastive learning and domain adaptation(SSMCL-DA)method for gearbox fault diagnosis under variable conditions.Initially,during the unsupervised pre-training phase,a dual signal augmentation strategy is devised,which simultaneously applies random masking in the time domain and random scaling in the frequency domain to unlabeled samples,thereby constructing more challenging positive sample pairs to guide the encoder in learning intrinsic features robust to condition variations.Subsequently,a ConvNeXt-Transformer hybrid architecture is employed,integrating the superior local detail modeling capacity of ConvNeXt with the robust global perception capability of Transformer to enhance feature extraction in complex scenarios.Thereafter,a contrastive learning model is constructed with the optimization objective of maximizing feature similarity across different masked instances of the same sample,enabling the extraction of consistent features from multiple masked perspectives and reducing reliance on labeled data.In the final supervised fine-tuning phase,a multi-scale attention mechanism is incorporated for feature rectification,and a domain adaptation module combining Local Maximum Mean Discrepancy(LMMD)with adversarial learning is proposed.This module embodies a dual mechanism:LMMD facilitates fine-grained class-conditional alignment,compelling features of identical fault classes to converge across varying conditions,while the domain discriminator utilizes adversarial training to guide the feature extractor toward learning domain-invariant features.Working in concert,they markedly diminish feature distribution discrepancies induced by changes in load,rotational speed,and other factors,thereby boosting the model’s adaptability to cross-condition scenarios.Experimental evaluations on the WT planetary gearbox dataset and the Case Western Reserve University(CWRU)bearing dataset demonstrate that the SSMCL-DA model effectively identifies multiple fault classes in gearboxes,with diagnostic performance substantially surpassing that of conventional methods.Under cross-condition scenarios,the model attains fault diagnosis accuracies of 99.21%for the WT planetary gearbox and 99.86%for the bearings,respectively.Furthermore,the model exhibits stable generalization capability in cross-device settings.展开更多
Drill string vibration during drilling plays a vital and potentially decisive role in maintaining wellbore stability,as repeated impacts may lead to fatigue and borehole collapse.While drilling through geological laye...Drill string vibration during drilling plays a vital and potentially decisive role in maintaining wellbore stability,as repeated impacts may lead to fatigue and borehole collapse.While drilling through geological layers,a material contrast may act as a localization point for wellbore damage.The hypothesis tested in this paper is that wellbore instability is focused on the boundary between the layers and that mechanical contrasts accelerate the wellbore collapse.In this study,an elastic-plastic damage model was employed to investigate the effects of repeated mechanical impacts on wellbore stability.A 2-dimensional(2D)model of a wellbore surrounded by contrasting materials was developed,and the accumulated damage caused by repeated lateral impacts was monitored.It was found that damage develops not only around the wall of the wellbore but also along the material boundaries.A sensitivity analysis was carried out to identify the impact of contrasts in both elastic(Young's modulus and Poisson's ratio)and plastic(cohesion,friction angle,and dilation angle)parameters between layers.Four damage patterns were identifiedin the simulated models.The results also suggested that the number of impacts required to reach the critical damage was highly affected by the contrast in elastic parameters,while cohesion and friction angle contrasts had a lesser effect.Additionally,increasing the contrast in the dilation angle localized the damage,thus reducing the number of impacts required to trigger wellbore failure.展开更多
Lacustrine groundwater discharge(LGD)plays an important role in water resources management.Previous studies have focused on LGD process in a single lake,but the differences in LGD process within the same region have n...Lacustrine groundwater discharge(LGD)plays an important role in water resources management.Previous studies have focused on LGD process in a single lake,but the differences in LGD process within the same region have not been thoroughly investigated.In this study,multiple tracers(hydrochemistry,𝛿D,𝛿18O and 222Rn)were used to compare mechanisms of LGD in Daihai and Ulansuhai Lake in Inner Mongoli1,Northwest China.The hydrochemical types showed a trend from groundwater to lake water,indicating a hydraulic connection between them.In addition,the𝛿D and𝛿18O values of sediment pore water were between the groundwater and lake water,indicating the LGD processes.The radon mass balance model was used to estimate the average groundwater discharge rates of Daihai and Ulansuhai Lake,which were 2.79 mm/day and 3.02 mm/day,respectively.The total nitrogen(TN),total phosphorus(TP),and fluoride inputs associated with LGD in Daihai Lake accounted for 97.52%,96.59%,and 95.84%of the total inputs,respectively.In contrast,TN,TP and fluoride inputs in Ulansuhai Lake were 53.56%,40.98%,and 36.25%,respectively.This indicates that the pollutant inputs associated with LGD posed a potential threat to the ecological stability of Daihai and Ulansuhai Lake.By comparison,the differences of LGD process and associated pollutant flux were controlled by hydrogeological conditions,lakebed permeability and human activities.This study provides a reference for water resources management in Daihai and Ulansuhai Lake basins while improving the understanding of LGD in the Yellow River basin.展开更多
The chemical structure of polyamide 6(PA6)dictates that only 50%of hydrogen bonds participate in crystallization during the crystallization process,resulting in the properties of its products being significantly depen...The chemical structure of polyamide 6(PA6)dictates that only 50%of hydrogen bonds participate in crystallization during the crystallization process,resulting in the properties of its products being significantly dependent on the molding process.Therefore,the design and development of nucleating agents suitable for PA6 holds great practical significance for high-performance PA6 materials.Amide-based nucleating agents can effectively improve the crystallization rate by increasing intermolecular hydrogen bond density.Further introduction of hydroxyl groups can enhance the hydrogen bonding interactions between the nucleating agent and PA6.In this study,a hydroxyl-containing amidebased nucleating agent,BHT,was designed and synthesized using a tyramine-based biomass as the raw material.These results demonstrated that BHT exhibited good structural compatibility with PA6.After adding 1 wt%BHT,the crystallization temperature of PA6 increased from 170.9℃to 193.3℃,the crystallinity increased 16.6%,the heat distortion temperature and Vicat softening temperature rose to 89.5 and 187.8℃,respectively,the haze decreased to 46%,achieving the synergistic optimization of mechanical,thermal,and optical properties.The in situ time-resolved FTIR results indicated that the addition of BHT increased the enthalpy of hydrogen bond formation during the nucleation stage,facilitated the segmental conformation adjustment of PA6,and enhanced the molar concentration of trans-conformations,ultimately leading to an improvement in the crystallization rate.展开更多
The crystallization and aggregation characteristics of the active layer components in organic solar cells(OSCs)are one of the core factors determining photovoltaic performance,influencing the entire process from light...The crystallization and aggregation characteristics of the active layer components in organic solar cells(OSCs)are one of the core factors determining photovoltaic performance,influencing the entire process from light absorption to charge separation,transport,and ultimately charge collection.Dynamic changes in crystallization and aggregation states can also disrupt the microstructure of the active layer,thus shortening the lifetime of the cell.In this study,a morphology modulation strategy is proposed to regulate the crystallization kinetics of non-fullerene acceptors by employing the polymer molecule PYIT as a nucleating agent.An appropriate amount of PYIT was first completely dissolved with the non-fullerene acceptor Y6 and left to stand for 24 h,followed by the fabrication of layer-by-layer processed OSCs.Experiments demonstrated that high crystallinity of PYIT allows it to act as a crystallization nucleus,promoting the crystallization,orientation consistency,and ordered stacking of the acceptor.These nanoscale structural optimizations facilitate efficient charge transport,enhance exciton dissociation efficiency,and suppress unfavorable energetic disorder.Consequently,not only was the power conversion efficiency(PCE)of D18-Cl/Y6-based layer-by-layer processed OSC increased from 18.08%to 19.13%,but the atmospheric stability and long-term lifetime of the OSCs were also significantly improved.Notably,this strategy is also applicable to indoor OSCs,and the PYIT-optimized device can achieve a PCE of 27.0%under 1000 lux light-emitting diode(LED,3200K)irradiation,which is superior to that of the control device(24.2%).This work develops a crystal engineering strategy that is able to simultaneously optimize the microscopic morphology and charge dynamics properties in OSCs,thereby achieving simultaneous improvement in efficiency and stability.展开更多
With the rise of AI-assisted education,many instructors and engineers seek to deliver high-quality programming courses online.However,crafting effective programming lectures remains a challenge,particularly for instru...With the rise of AI-assisted education,many instructors and engineers seek to deliver high-quality programming courses online.However,crafting effective programming lectures remains a challenge,particularly for instructors lacking pedagogical training or multilingual fluency.We present CourseAgent,a prompt-driven framework that leverages large language models(LLMs)to automatically generate Python tutorials,structured lecture scripts,and accompanying audio narrations.CourseAgent accepts raw code as input and transforms it into segmented,well-commented code blocks,adapting content to different difficulty levels and languages via prompt customization.Our system supports multilingual instruction(e.g.,Chinese,English),fine-grained control of pedagogical depth,and auto-generation of lecture videos.We evaluate the output generated by CourseAgent using real student feedback and feedback from in-service teachers,alongside automated assessments from LLMs.These evaluations demonstrate that the materials produced by CourseAgent are coherent,pedagogically sound,and comparable in quality to those created by experienced instructors.CourseAgent lowers the barrier to quality programming education and shows promise for scalable,personalized,and language-adaptive content generation.展开更多
Industrial waste salts are commonly used to make value-added snow-melting agents to ensure traffic safety in northern China during winter and spring after snowfall.However,heavy metals in industrial waste salts may po...Industrial waste salts are commonly used to make value-added snow-melting agents to ensure traffic safety in northern China during winter and spring after snowfall.However,heavy metals in industrial waste salts may pose certain environmental risks.Snow-melting agents and snow samples were collected and analyzed from highways,arterial roads,footbridges,and other locations in Beijing after the snowstorm in December 2023.It was found that the main component of snow-melting agents was sodium chloride with high concentrations of Cu,Mn,and Zn,which are not regulated in the current policies,despite the recent promotion of environmentally friendly snow-melting agents.The Pb,Zn and Cr contents of some snow samples exceeded the limitation value of surface water quality standards,potentially affecting the soil and water environment near roadsides,although the snow-melting agents comply with relevant standards,which indicates the policy gap in the management of recycled industrial salts.We reviewed and analyzed the relevant standards for snow-melting agents and industrial waste salts proposed nationally and internationally over the past 30 years.Through comparative analysis,we proposed relevant policy recommendations to the existing quality standards of snow-melting agents and the management regulations of industrial waste salts,and the formulation of corresponding usage strategies,aimed at reducing the potential environmental release of heavy metals from the use of snow-melting agents,thereby promoting more sustainable green urban development and environmentally sound waste management.展开更多
文摘Conventional echocardiography can sometimes pose a challenge to diagnosis due to sub-optimal images.Ultrasound contrast agents(UCAs)have been shown to drastically enhance imaging quality,particularly depicting the left ventricular endocardial borders.Their use during echocardiography has become a valuable tool in non-invasive diagnostics.UCAs provide higher-quality images that may ultimately reduce the length of hospital stays and improve patient care.The higher cost associated with UCAs in many situations has been an impediment to frequent use.However,when used as an initial diagnostic test,UCA during rest echocardiogram is more cost-effective than the traditional diagnostic approach,which frequently includes multiple tests and imaging studies to make an accurate diagnosis.They can be easily performed across multiple patient settings and provide optimal images that allow clinicians to make sound medical decisions.This consequently allows for better diagnostic accuracies and improvement in patient care.
基金Project supported by the National Natural Science Foundation of China(82304311,81903460)the Sichuan Province Science and Technology Program(2022YFS0616)。
文摘Spectral computed tomography(CT)imaging as an advanced and non-invasive technique is of importance in the diagnosis of disease.Therefore,it is significant to develop safe and high-performance contrast agents for spectral CT imaging.Herein,we synthesized a small-molecule erbium chelate(ErDOTA dimeglumine),with the advantages of favorable colloidal and structure stability,good biocompatibility and biosafety,and sensitive spectral CT imaging ability in vitro and in vivo.Erbium chelate exhibits strong X-ray attenuation capability and the energy-dependent attenuation in the range of 40-160 keV due to the high K-edge value of Er(57.5 keV).Especially,the slope of the Hounsfield unit(HU)curve for erbium chelate is 1.5 times that of iohexol at 50 keV,and 5.6 times that of iohexol at130 keV.We then applied erbium chelate in the in vivo spectral CT imaging of healthy mice and DSSinduced colitis mice.It is found that erbium chelate is rapidly metabolized from the intestinal tract in healthy mice within 12 h due to favorable biocompatibility,while it is enriched and displays brighter signals in the inflammatory site of colon in colitis mice.Specifically,the CT value in the large intestines of colitis mice 12 h after erbium chelate administration is 53.0,which is much higher than that of healthy mice(8.3),showing great potential for sensitive and accurate diagnosis of inflammatory bowel disease.Moreover,compared with the clinically used contrast agent iohexol,erbium chelate shows better spectral CT imaging performance in both healthy and colitis mice at low to high energy settings.Superior CT imaging is also observed in CT26 tumor-bearing mice after administration with erbium chelate in comparison to iohexol.In summary,the small-molecule erbium chelate is expected to be a safe and highperfo rmance co ntrast agent for spectral CT imaging to promote the diagnosis of gastrointestinal diseases.
文摘Ultrasmall superparamagnetic iron oxide nanoparticles(usSPIONs)are promising alternatives to gadolinium‐based contrast agents for positive contrast enhancement in magnetic resonance imaging(MRI).Unlike larger SPIONs that primarily function as T2/T2*negative contrast agents,usSPIONs with core diameters below 5 nm can effectively shorten T1 relaxation times,producing bright signals in T1‐weighted images.This distinct behavior stems from their unique magnetic properties,including single‐domain configurations,surface spin canting,and rapid Néel relaxation dynamics,which are particularly enhanced at low magnetic field strengths.The biocompatibility of iron oxide,efficient renal clearance pathways,and versatility for surface functionalization offer potential advantages over gadolinium‐based agents,especially regarding safety concerns related to nephrogenic systemic fibrosis and gadolinium deposition.These nanoparticles show particular promise for applications in lowfield MRI,vascular imaging,targeted molecular imaging,and theranostic platforms.Although challenges remain in optimizing synthesis methods for consistent production of monodisperse usSPIONs with tailored surface chemistry,ongoing research continues to advance their potential for clinical translation.This review explores the mechanisms,synthesis approaches,applications,and future perspectives of usSPIONs as positive contrast agents in MRI.
基金the FRC grant(UBD/RSCH/1.4/FICBF(b)/2023/059)received from Universiti Brunei Darussalam,Brunei Darussalam。
文摘The syntheses of Gd(OH)_(3)and Gd(OH)_(3)-based nanomaterials have been reported and these materials have been developed as excellent MRI contrast agents.Due to the close interrelation between their morphology and properties,it has resulted in the development of various particle sizes and shapes of Gd(OH)_(3)and Gd(OH)_(3)-based nanomaterials.This has led to the extension of the uses of the materials to photocatalysis,drug delivery,and CT image contrast agents.Accordingly,these applications have been compiled and discussed in depth in this review.The potential of these materials in the above applications has started to attract significant attention.Moreover,the compilation of in-vitro toxicity studies from the literature was also discussed to facilitate the biocompatibility of the developed Gd(OH)_(3)nanomaterials.However,despite the rapid progress of Gd(OH)_(3)and Gd(OH)_(3)-based nanomaterials,there are still knowledge gaps in certain areas.Therefore,this review provides insights into the recent development of Gd(OH)_(3)and Gd(OH)_(3)-based nanomaterials to aid in accelerating novel developments.
基金supported by the Ministry of Education and Science of the Republic of North Macedonia through the project“Utilizing AI and National Large Language Models to Advance Macedonian Language Capabilties”。
文摘Artificial intelligence(AI)is reshaping financial systems and services,as intelligent AI agents increasingly form the foundation of autonomous,goal-driven systems capable of reasoning,learning,and action.This review synthesizes recent research and developments in the application of AI agents across core financial domains.Specifically,it covers the deployment of agent-based AI in algorithmic trading,fraud detection,credit risk assessment,roboadvisory,and regulatory compliance(RegTech).The review focuses on advanced agent-based methodologies,including reinforcement learning,multi-agent systems,and autonomous decision-making frameworks,particularly those leveraging large language models(LLMs),contrasting these with traditional AI or purely statistical models.Our primary goals are to consolidate current knowledge,identify significant trends and architectural approaches,review the practical efficiency and impact of current applications,and delineate key challenges and promising future research directions.The increasing sophistication of AI agents offers unprecedented opportunities for innovation in finance,yet presents complex technical,ethical,and regulatory challenges that demand careful consideration and proactive strategies.This review aims to provide a comprehensive understanding of this rapidly evolving landscape,highlighting the role of agent-based AI in the ongoing transformation of the financial industry,and is intended to serve financial institutions,regulators,investors,analysts,researchers,and other key stakeholders in the financial ecosystem.
基金supported by the National Natural Science Foundation of China Funded Project(Project Name:Research on Robust Adaptive Allocation Mechanism of Human Machine Co-Driving System Based on NMS Features,Project Approval Number:52172381).
文摘To address the issue of scarce labeled samples and operational condition variations that degrade the accuracy of fault diagnosis models in variable-condition gearbox fault diagnosis,this paper proposes a semi-supervised masked contrastive learning and domain adaptation(SSMCL-DA)method for gearbox fault diagnosis under variable conditions.Initially,during the unsupervised pre-training phase,a dual signal augmentation strategy is devised,which simultaneously applies random masking in the time domain and random scaling in the frequency domain to unlabeled samples,thereby constructing more challenging positive sample pairs to guide the encoder in learning intrinsic features robust to condition variations.Subsequently,a ConvNeXt-Transformer hybrid architecture is employed,integrating the superior local detail modeling capacity of ConvNeXt with the robust global perception capability of Transformer to enhance feature extraction in complex scenarios.Thereafter,a contrastive learning model is constructed with the optimization objective of maximizing feature similarity across different masked instances of the same sample,enabling the extraction of consistent features from multiple masked perspectives and reducing reliance on labeled data.In the final supervised fine-tuning phase,a multi-scale attention mechanism is incorporated for feature rectification,and a domain adaptation module combining Local Maximum Mean Discrepancy(LMMD)with adversarial learning is proposed.This module embodies a dual mechanism:LMMD facilitates fine-grained class-conditional alignment,compelling features of identical fault classes to converge across varying conditions,while the domain discriminator utilizes adversarial training to guide the feature extractor toward learning domain-invariant features.Working in concert,they markedly diminish feature distribution discrepancies induced by changes in load,rotational speed,and other factors,thereby boosting the model’s adaptability to cross-condition scenarios.Experimental evaluations on the WT planetary gearbox dataset and the Case Western Reserve University(CWRU)bearing dataset demonstrate that the SSMCL-DA model effectively identifies multiple fault classes in gearboxes,with diagnostic performance substantially surpassing that of conventional methods.Under cross-condition scenarios,the model attains fault diagnosis accuracies of 99.21%for the WT planetary gearbox and 99.86%for the bearings,respectively.Furthermore,the model exhibits stable generalization capability in cross-device settings.
基金support from the Research Council of Norway,Equinor,and Sekal with NFR project(Grant No.308826).
文摘Drill string vibration during drilling plays a vital and potentially decisive role in maintaining wellbore stability,as repeated impacts may lead to fatigue and borehole collapse.While drilling through geological layers,a material contrast may act as a localization point for wellbore damage.The hypothesis tested in this paper is that wellbore instability is focused on the boundary between the layers and that mechanical contrasts accelerate the wellbore collapse.In this study,an elastic-plastic damage model was employed to investigate the effects of repeated mechanical impacts on wellbore stability.A 2-dimensional(2D)model of a wellbore surrounded by contrasting materials was developed,and the accumulated damage caused by repeated lateral impacts was monitored.It was found that damage develops not only around the wall of the wellbore but also along the material boundaries.A sensitivity analysis was carried out to identify the impact of contrasts in both elastic(Young's modulus and Poisson's ratio)and plastic(cohesion,friction angle,and dilation angle)parameters between layers.Four damage patterns were identifiedin the simulated models.The results also suggested that the number of impacts required to reach the critical damage was highly affected by the contrast in elastic parameters,while cohesion and friction angle contrasts had a lesser effect.Additionally,increasing the contrast in the dilation angle localized the damage,thus reducing the number of impacts required to trigger wellbore failure.
基金supported by the Natural Science Foundation of Inner Mongolia Autonomous Region of China(No.2023QN04011)the National Natural Science Foundation of China(Nos.42307092 and 52279067)+1 种基金Ordos Science and Technology Major Project(No.ZD20232303)Project of Key Laboratory of River and Lake in Inner Mongolia Autonomous Region(No.2022QZBZ0003).
文摘Lacustrine groundwater discharge(LGD)plays an important role in water resources management.Previous studies have focused on LGD process in a single lake,but the differences in LGD process within the same region have not been thoroughly investigated.In this study,multiple tracers(hydrochemistry,𝛿D,𝛿18O and 222Rn)were used to compare mechanisms of LGD in Daihai and Ulansuhai Lake in Inner Mongoli1,Northwest China.The hydrochemical types showed a trend from groundwater to lake water,indicating a hydraulic connection between them.In addition,the𝛿D and𝛿18O values of sediment pore water were between the groundwater and lake water,indicating the LGD processes.The radon mass balance model was used to estimate the average groundwater discharge rates of Daihai and Ulansuhai Lake,which were 2.79 mm/day and 3.02 mm/day,respectively.The total nitrogen(TN),total phosphorus(TP),and fluoride inputs associated with LGD in Daihai Lake accounted for 97.52%,96.59%,and 95.84%of the total inputs,respectively.In contrast,TN,TP and fluoride inputs in Ulansuhai Lake were 53.56%,40.98%,and 36.25%,respectively.This indicates that the pollutant inputs associated with LGD posed a potential threat to the ecological stability of Daihai and Ulansuhai Lake.By comparison,the differences of LGD process and associated pollutant flux were controlled by hydrogeological conditions,lakebed permeability and human activities.This study provides a reference for water resources management in Daihai and Ulansuhai Lake basins while improving the understanding of LGD in the Yellow River basin.
文摘The chemical structure of polyamide 6(PA6)dictates that only 50%of hydrogen bonds participate in crystallization during the crystallization process,resulting in the properties of its products being significantly dependent on the molding process.Therefore,the design and development of nucleating agents suitable for PA6 holds great practical significance for high-performance PA6 materials.Amide-based nucleating agents can effectively improve the crystallization rate by increasing intermolecular hydrogen bond density.Further introduction of hydroxyl groups can enhance the hydrogen bonding interactions between the nucleating agent and PA6.In this study,a hydroxyl-containing amidebased nucleating agent,BHT,was designed and synthesized using a tyramine-based biomass as the raw material.These results demonstrated that BHT exhibited good structural compatibility with PA6.After adding 1 wt%BHT,the crystallization temperature of PA6 increased from 170.9℃to 193.3℃,the crystallinity increased 16.6%,the heat distortion temperature and Vicat softening temperature rose to 89.5 and 187.8℃,respectively,the haze decreased to 46%,achieving the synergistic optimization of mechanical,thermal,and optical properties.The in situ time-resolved FTIR results indicated that the addition of BHT increased the enthalpy of hydrogen bond formation during the nucleation stage,facilitated the segmental conformation adjustment of PA6,and enhanced the molar concentration of trans-conformations,ultimately leading to an improvement in the crystallization rate.
基金supported by the National Natural Science Foundation of China (NSFC grant no. 62474028, 52130304, and62222503)the Natural Science Foundation of Sichuan Province(2025ZNSFSC0037, 2025ZNSFSC1460, and 2024NSFSC1447)+1 种基金the National Key R and D Program of China (2023YFB2604101)sponsored by the Sichuan Province Key Laboratory of Display Science and Technology
文摘The crystallization and aggregation characteristics of the active layer components in organic solar cells(OSCs)are one of the core factors determining photovoltaic performance,influencing the entire process from light absorption to charge separation,transport,and ultimately charge collection.Dynamic changes in crystallization and aggregation states can also disrupt the microstructure of the active layer,thus shortening the lifetime of the cell.In this study,a morphology modulation strategy is proposed to regulate the crystallization kinetics of non-fullerene acceptors by employing the polymer molecule PYIT as a nucleating agent.An appropriate amount of PYIT was first completely dissolved with the non-fullerene acceptor Y6 and left to stand for 24 h,followed by the fabrication of layer-by-layer processed OSCs.Experiments demonstrated that high crystallinity of PYIT allows it to act as a crystallization nucleus,promoting the crystallization,orientation consistency,and ordered stacking of the acceptor.These nanoscale structural optimizations facilitate efficient charge transport,enhance exciton dissociation efficiency,and suppress unfavorable energetic disorder.Consequently,not only was the power conversion efficiency(PCE)of D18-Cl/Y6-based layer-by-layer processed OSC increased from 18.08%to 19.13%,but the atmospheric stability and long-term lifetime of the OSCs were also significantly improved.Notably,this strategy is also applicable to indoor OSCs,and the PYIT-optimized device can achieve a PCE of 27.0%under 1000 lux light-emitting diode(LED,3200K)irradiation,which is superior to that of the control device(24.2%).This work develops a crystal engineering strategy that is able to simultaneously optimize the microscopic morphology and charge dynamics properties in OSCs,thereby achieving simultaneous improvement in efficiency and stability.
基金supported by the Zhejiang Province Leading Geese Plan(Grant No.2025C02025)the Guangdong Province Primary and Secondary School Teachers’Digital Literacy Enhancement Project 2025(Grant No.GDSZSYKT2025244).
文摘With the rise of AI-assisted education,many instructors and engineers seek to deliver high-quality programming courses online.However,crafting effective programming lectures remains a challenge,particularly for instructors lacking pedagogical training or multilingual fluency.We present CourseAgent,a prompt-driven framework that leverages large language models(LLMs)to automatically generate Python tutorials,structured lecture scripts,and accompanying audio narrations.CourseAgent accepts raw code as input and transforms it into segmented,well-commented code blocks,adapting content to different difficulty levels and languages via prompt customization.Our system supports multilingual instruction(e.g.,Chinese,English),fine-grained control of pedagogical depth,and auto-generation of lecture videos.We evaluate the output generated by CourseAgent using real student feedback and feedback from in-service teachers,alongside automated assessments from LLMs.These evaluations demonstrate that the materials produced by CourseAgent are coherent,pedagogically sound,and comparable in quality to those created by experienced instructors.CourseAgent lowers the barrier to quality programming education and shows promise for scalable,personalized,and language-adaptive content generation.
基金supported by the National Natural Science Foundation of China(No.22176200)the Industrial Innovation Entrepreneurial Team Project of Ordos 2021.
文摘Industrial waste salts are commonly used to make value-added snow-melting agents to ensure traffic safety in northern China during winter and spring after snowfall.However,heavy metals in industrial waste salts may pose certain environmental risks.Snow-melting agents and snow samples were collected and analyzed from highways,arterial roads,footbridges,and other locations in Beijing after the snowstorm in December 2023.It was found that the main component of snow-melting agents was sodium chloride with high concentrations of Cu,Mn,and Zn,which are not regulated in the current policies,despite the recent promotion of environmentally friendly snow-melting agents.The Pb,Zn and Cr contents of some snow samples exceeded the limitation value of surface water quality standards,potentially affecting the soil and water environment near roadsides,although the snow-melting agents comply with relevant standards,which indicates the policy gap in the management of recycled industrial salts.We reviewed and analyzed the relevant standards for snow-melting agents and industrial waste salts proposed nationally and internationally over the past 30 years.Through comparative analysis,we proposed relevant policy recommendations to the existing quality standards of snow-melting agents and the management regulations of industrial waste salts,and the formulation of corresponding usage strategies,aimed at reducing the potential environmental release of heavy metals from the use of snow-melting agents,thereby promoting more sustainable green urban development and environmentally sound waste management.
