Infrared thermography has been widely applied in real industrial inspection of aerospace,energy management systems,engines,and electric systems.However,two-dimensional imaging modality limits its development.Here,a te...Infrared thermography has been widely applied in real industrial inspection of aerospace,energy management systems,engines,and electric systems.However,two-dimensional imaging modality limits its development.Here,a technique named frequency multiplexed photothermal correlation tomography(FM-PCT)was developed to enable non-destructive and contactless cross-sectional imaging for manufactured material evaluation and characterization.By combining advantages of photothermal tomography and pulsed thermography,FM-PCT facilitates the generation of three-dimensional thermal images through temporal superposition(stacking)of two-dimensional images from sequential subsurface depths.FM-PCT image processing involves pulsed excitation signals to which frequency delay and matched filtering techniques are applied.Major features of FM-PCT are high-resolution three-dimensional tomographic imaging under low camera frame-rate conditions with self-correcting capability for diffusion(blurring)correction of subsurface images due to cross-correlation processing of individual frequencies in the Fourier decomposition spectrum of the excitation pulse.Furthermore,FM-PCT extends truncated-correlation photothermal coherence tomography from chirp and pulsed signals to more general linear heating sources.Lock-in thermography and x-ray computed tomography validation demonstrate that 3D FM-PCT imaging accurately reveals subsurface discontinuities/defects in solids despite the diffusive nature of thermal-wave imaging.展开更多
In recent years, advanced composite structures are used extensively in many industries such as aerospace, aircraft, automobile, pipeline and civil engineering. Reliability and safety are crucial requirements posed by ...In recent years, advanced composite structures are used extensively in many industries such as aerospace, aircraft, automobile, pipeline and civil engineering. Reliability and safety are crucial requirements posed by them to the advanced composite structures be- cause of their harsh working conditions. Therefore, as a very important measure, structural health monitoring （SHM） in-service is deft- nitely demanded for ensuring their safe working in-situ. In this paper, fiber Bragg grating （FBG） sensors are surface-mounted on the hoop and in the axial directions of a FRP pressure vessel to monitor the strain status during its pressurization. The experimental results show that the FBG sensors could be used to monitor the strain development and determine the ultimate failure strain of the composite pressure vessel.展开更多
This paper introduces recent research work in the field of pulsed electromagnetic non-destructive testing/evaluation.These are pulsed eddy current,pulsed magnetic flux leakage and eddy current pulsed thermography.This...This paper introduces recent research work in the field of pulsed electromagnetic non-destructive testing/evaluation.These are pulsed eddy current,pulsed magnetic flux leakage and eddy current pulsed thermography.This paper introduces pulsed electromagnetic techniques and their different case studies on defect detection as well as stress characterisation.Experimental tests have been validated and future research plans are discussed.This paper demonstrates pulsed electromagnetic non-destructive testing and evaluation for not only depth information,but also for multiple parameter measurement and multiple integration,which are important for future development.展开更多
This article should not be considered as a full review of current methods for non-destructive testing of surface layers. Rather, it is a subjective in this area. However, the article provides some review of the challe...This article should not be considered as a full review of current methods for non-destructive testing of surface layers. Rather, it is a subjective in this area. However, the article provides some review of the challenges posed by the current state of surface layers treatment techniques on the area of Non-Destructive materials evaluation: enhancement of the sensitivity to the type of defects, increasing resolution to submicron values, the requirement to diagnose the surface layers with depth resolution of properties, diagnosis of multilayer multicomponent surface layers and coatings, treated with concentrated energy.展开更多
Non-destructive measurement of absolute stress in steel members can provide useful information to optimize the design of steel structures and allow the safety of existing structures to be evaluated.This paper investig...Non-destructive measurement of absolute stress in steel members can provide useful information to optimize the design of steel structures and allow the safety of existing structures to be evaluated.This paper investigates the non-destructive capability of ultrasonic shear-wave spectroscopy in absolute stress evaluation of steel members.The effect of steel-member stress on the shear-wave amplitude spectrum is investigated,and a method of absolute stress measurement is proposed.Specifically,the process for evaluating absolute stress using shear-wave spectroscopy is summarized.Two steel members are employed to investigate the relationship between the stress and the frequency in shear-wave echo amplitude spectrum.The H-beam loaded by the universal testing machine is evaluated by the proposed method and the traditional strain gauge method for verification.The results show that the proposed method is effective and accurate for determining absolute stress in steel members.展开更多
Composite materials are increasingly used in the aerospace and automotive industries due to their high strength-toweight ratio and fatigue resistance.These structures may develop internal defects during manufacturing ...Composite materials are increasingly used in the aerospace and automotive industries due to their high strength-toweight ratio and fatigue resistance.These structures may develop internal defects during manufacturing or service,compromising their integrity and safety.Thus,non-destructive defect detection is critical during production to ensure safety and reliability.This study explores the application of terahertz time-domain spectroscopy(THz-TDS)for detecting damage in different glass fiber-reinforced polymer(GFRP)manufacturing processes.A cross-correlation-based impulse response function extraction algorithm and image enhancement method are proposed.The method targets both deep and minor defects in GFRP,leveraging the correlation between the terahertz reference signal and the time-domain detection signal to extract the terahertz impulse response function via a one-dimensional iterative deconvolution algorithm.Testing on samples with pre-fabricated delamination,three-point bending damage,and drilled damage demonstrated the method’s efficacy in extracting impulse response functions of delamination defects,which aids in defect localization and improved image representation.In the THz imaging analysis of GFRP manufacturing process damage,signal alignment,windowing,and morphology positioning techniques were applied based on the extracted impulse response functions.The proposed method significantly improved the quality of THz images for defect detection in GFRP,as demonstrated by objective evaluations and comparisons.These advancements provide a robust and effective tool for the non-destructive evaluation of composite materials.展开更多
Longitudinal joint construction quality is critical to the life of flexible pavements.Maintaining deteriorated longitudinal joints has become a challenge for many highway agencies.Improving the joint's quality thr...Longitudinal joint construction quality is critical to the life of flexible pavements.Maintaining deteriorated longitudinal joints has become a challenge for many highway agencies.Improving the joint's quality through better compaction during construction can help achieve flexible pavements with longer service lives and less maintenance.Current quality control(QC)and quality assurance(QA)plans provide limited coverage.Consequently,the risk of missing areas with poor joint compaction is significant.A density profiling system(DPS)is a non-destructive alternative to conventional destructive evaluation methods.It can provide quick and continuous real-time coverage of the compaction during construction in dielectrics.The paper presents several case studies comparing various types of longitudinal joints and demonstrating the use of DPS to evaluate the joint's compaction quality.The paper shows that dielectric measurements can provide valuable insight into the ability of various construction techniques to achieve adequate levels of compaction at the longitudinal joint.The paper proposes a dielectric-based longitudinal joint quality index(LJQI)to evaluate the relative compaction of the joint during construction.It also shows that adopting DPS for assessing the compaction of longitudinal joints can minimize the risk of agencies accepting poorly constructed joints,identify locations of poor quality during construction,and achieve better-performing flexible pavements.展开更多
Pulsed eddy current （PEC） non-destructive test- ing and evaluation （NDT＆E） has been around for some time and it is still attracting extensive attention from researchers around the globe, which can be witnessed th...Pulsed eddy current （PEC） non-destructive test- ing and evaluation （NDT＆E） has been around for some time and it is still attracting extensive attention from researchers around the globe, which can be witnessed through the reports reviewed in this paper. Thanks to its richness of spectral components, various applications of this technique have been proposed and reported in the lit- erature covering both structural integrity inspection and material characterization in various industrial sectors. To support its development and for better understanding of the phenomena around the transient induced eddy currents, attempts for its modelling both analytically and numeri- cally have been made by researchers around the world. This review is an attempt to capture the state-of-the-art development and applications of PEC, especially in the last 15 years and it is not intended to be exhaustive. Future challenges and opportunities for PEC NDT＆E are also presented.展开更多
Although machine Learning has demonstrated exceptional applicability in thermographic inspection,precise defect reconstruction is still challenging,especially for complex defect profiles with limited defect sample div...Although machine Learning has demonstrated exceptional applicability in thermographic inspection,precise defect reconstruction is still challenging,especially for complex defect profiles with limited defect sample diversity.Thus,this paper proposes a self-enhancement defect reconstruction technique based on cycle-consistent generative adversarial network(Cycle-GAN)that accurately characterises complex defect profiles and generates reliable artificial thermal images for dataset augmentation,enhancing defect characterisation.By using a synthetic dataset from simulation and experiments,the network overcomes the limited samples problem by learning the diversity of complex defects from finite element modelling and obtaining the thermography uncertainty patterns from practical experiments.Then,an iterative strategy with a self-enhancement capability optimises the characterisation accuracy and data generation performance.The designed loss function structure with cycle consistency and identity loss constrains the GAN’s transfer variation to guarantee augmented data quality and defect reconstruction accuracy simultaneously,while the self-enhancement results significantly improve accuracy in thermal images and defect profile reconstruction.The experimental results demonstrate the feasibility of the proposed method by attaining high accuracy with optimal loss norm for defect profile reconstruction with a Recall score over 0.92.The scalability investigation of different materials and defect types is also discussed,highlighting its capability for diverse thermography quantification and automated inspection scenarios.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
BACKGROUND Coronavirus disease 2019(COVID-19)disrupted healthcare and led to increased telehealth use.We explored the impact of COVID-19 on liver transplant evaluation(LTE).AIM To understand the impact of telehealth o...BACKGROUND Coronavirus disease 2019(COVID-19)disrupted healthcare and led to increased telehealth use.We explored the impact of COVID-19 on liver transplant evaluation(LTE).AIM To understand the impact of telehealth on LTE during COVID-19 and to identify disparities in outcomes disaggregated by sociodemographic factors.METHODS This was a retrospective study of patients who initiated LTE at our center from 3/16/20-3/16/21(“COVID-19 era”)and the year prior(3/16/19-3/15/20,“pre-COVID-19 era”).We compared LTE duration times between eras and explored the effects of telehealth and inpatient evaluations on LTE duration,listing,and pretransplant mortality.RESULTS One hundred and seventy-eight patients were included in the pre-COVID-19 era cohort and one hundred and ninety-nine in the COVID-19 era cohort.Twentynine percent(58/199)of COVID-19 era initial LTE were telehealth,compared to 0%(0/178)pre-COVID-19.There were more inpatient evaluations during COVID-19 era(40%vs 28%,P<0.01).Among outpatient encounters,telehealth use for initial LTE during COVID-19 era did not impact likelihood of listing,pretransplant mortality,or time to LTE and listing.Median times to LTE and listing during COVID-19 were shorter than pre-COVID-19,driven by increased inpatient evaluations.Sociodemographic factors were not predictive of telehealth.CONCLUSION COVID-19 demonstrates a shift to telehealth and inpatient LTE.Telehealth does not impact LTE or listing duration,likelihood of listing,or mortality,suggesting telehealth may facilitate LTE without negative outcomes.展开更多
Solid-state batteries are widely recognized as the next-generation energy storage devices with high specific energy,high safety,and high environmental adaptability.However,the research and development of solid-state b...Solid-state batteries are widely recognized as the next-generation energy storage devices with high specific energy,high safety,and high environmental adaptability.However,the research and development of solid-state batteries are resource-intensive and time-consuming due to their complex chemical environment,rendering performance prediction arduous and delaying large-scale industrialization.Artificial intelligence serves as an accelerator for solid-state battery development by enabling efficient material screening and performance prediction.This review will systematically examine how the latest progress in using machine learning(ML)algorithms can be used to mine extensive material databases and accelerate the discovery of high-performance cathode,anode,and electrolyte materials suitable for solid-state batteries.Furthermore,the use of ML technology to accurately estimate and predict key performance indicators in the solid-state battery management system will be discussed,among which are state of charge,state of health,remaining useful life,and battery capacity.Finally,we will summarize the main challenges encountered in the current research,such as data quality issues and poor code portability,and propose possible solutions and development paths.These will provide clear guidance for future research and technological reiteration.展开更多
Subgrade engineering is a fundamental aspect of infrastructure construction in China.As the primary structural element responsible for bearing and distributing traffic loads,the subgrade must not only withstand the su...Subgrade engineering is a fundamental aspect of infrastructure construction in China.As the primary structural element responsible for bearing and distributing traffic loads,the subgrade must not only withstand the substantial pressures exerted by vehicles,trains,and other forms of transportation,but also efficiently transfer these loads to the underlying foundation,ensuring the stability and longevity of the roadway.In recent years,advancements in subgrade engineering technology have propelled the industry towards smarter,greener,and more sustainable practices,particularly in the areas of intelligent monitoring,disaster management,and innovative construction methods.This paper reviews the application and methodologies of intelligent testing equipment,including cone penetration testing(CPT)devices,soil resistivity testers,and intelligent rebound testers,in subgrade engineering.It examines the operating principles,advantages,limitations,and application ranges of these tools in subgrade testing.Additionally,the paper evaluates the practical use of advanced equipment from both domestic and international perspectives,addressing the challenges encountered by various instruments in realworld applications.These devices enable precise,comprehensive testing and evaluation of subgrade conditions at different stages,providing real-time data analysis and intelligent early warnings.This supports effective subgrade health management and maintenance.As intelligent technologies continue to evolve and integrate,these tools will increasingly enhance the accuracy,efficiency,and sustainability of subgrade monitoring.展开更多
China has abundant resources of hot dry rocks.However,due to the fact that the evaluation methods for favorable areas are mainly qualitative,and the evaluation indicators and standards are inconsistent,which restrict ...China has abundant resources of hot dry rocks.However,due to the fact that the evaluation methods for favorable areas are mainly qualitative,and the evaluation indicators and standards are inconsistent,which restrict the evaluation efficiency and exploration process of dry hot rocks.This paper is based on the understanding of the geologic features and genesis mechanisms of hot dry rocks in China and abroad.By integrating the main controlling factors of hot dry rock formation,and using index grading and quantification,the fuzzy hierarchical comprehensive method is applied to establish an evaluation system and standards for favorable areas of hot dry rocks.The evaluation system is based on four indicators:heat source,thermal channel,thermal reservoir and cap rock.It includes 11 evaluation parameters,including time of magmatic/volcanic activity,depth of molten mass or magma chamber,distribution of discordogenic faults,burial depth of thermal reservoir,cap rock type and thickness,surface thermal anomaly,heat flow,geothermal gradient,Moho depth,Curie depth,Earthquake magnitude and focal depth.Each parameter is divided into 3 levels.Applying this evaluation system to assess hot dry rock in central Inner Mongolia revealed that Class I favorable zones cover approximately 494 km^(2),while Class II favorable zones span about 5.7×10^(4) km^(2).The Jirgalangtu Sag and Honghaershute Sag in the Erlian Basin,along with Reshuitang Town in Keshiketeng Banner,Reshui Town in Ningcheng County,and Reshuitang Town in Aohan Banner of Chifeng City,are identified as Class I favorable zones for hot dry rock resources.These areas are characterized by high-temperature subsurface molten bodies or magma chambers serving as high-quality heat sources,shallow thermal reservoir depths,and overlying thick sedimentary rock layers acting as caprock.The establishment and application of the evaluation system for favorable areas of hot dry rock are expected to provide new approaches and scientific basis for guiding the practice of selecting hot dry rock areas in China.展开更多
OBJECTIVE:To evaluate the 10-year therapeutic efficacy of Traditional Chinese Medicine(TCM)using the Strengthening Spleen and Draining Dampness therapy in the management of idiopathic membranous nephropathy(IMN).METHO...OBJECTIVE:To evaluate the 10-year therapeutic efficacy of Traditional Chinese Medicine(TCM)using the Strengthening Spleen and Draining Dampness therapy in the management of idiopathic membranous nephropathy(IMN).METHODS:A single-center,retrospective analysis was conducted on patients diagnosed with IMN who met predefined inclusion and exclusion criteria.Data were collected from the Department of Nephrology at Longhua Hospital,affiliated with Shanghai University of Traditional Chinese Medicine,between January 2007 and December 2011.Clinical parameters including 24-h urinary protein,serum albumin,serum creatinine,and estimated glomerular filtration rate(e GFR,EPI)were assessed at baseline and at 1,3,5,and 10 years of follow-up.The efficacy of the Strengthening Spleen and Draining Dampness therapy was analyzed using repeated measures analysis of variance(ANOVA).Kaplan-Meier survival curves and multivariate proportional hazards model(Cox regression models)were employed to identify factors associated with treatment outcomes.RESULTS:A total of 265 patients were included,with a median follow-up duration of 96 months(36,122).TCM treatment significantly reduced 24-h urinary protein levels(P<0.001),and increased serum albumin levels(P<0.001),while serum creatinine remained stable(P=0.187).Remission rates at 1,3,5,and 10 years were 52.81%,69.71%,68.39%,and 72.36%,respectively,and the rates of avoiding composite outcome events at the same intervals were 98.27%,94.29%,94.19%,and 93.50%.In the subgroup receiving TCM only,remission rates were 56.67%,84.44%,76.32%,and 82.86%.For patients treated initially with Western Medicine followed by TCM,the rates were 52.83%,65.85%,67.47%and 67.75%.In the cohort of patients who received TCM as their first-line therapy,remission rates were 49.23%,62.50%,61.76%,and 69.23%.Multivariate Cox regression analysis revealed that the duration of TCM treatment[hazard ratio(HR)=0.826,95%confidence interval(CI)(0.779,0.876),P<0.001],presence of hypertension[HR=1.912,95%CI(1.181,3.094),P=0.008],baseline serum albumin level[HR=0.930,95%CI(0.894,0.969),P<0.001],and the rate of serum albumin increase within the first year of treatment[HR=0.930,95%CI(0.909,0.957),P<0.001]were significantly associated with clinical outcomes.CONCLUSION:The Strengthening Spleen and Draining Dampness therapy demonstrated robust short-and longterm efficacy in treating IMN,with high rates of remission and renal survival over 10 years.Key factors influencing clinical remission included the duration of TCM treatment,baseline serum albumin levels,the presence of hypertension,and the rate of increase in serum albumin within the first year.These findings suggest that this TCM approach provides a viable long-term treatment option for IMN.展开更多
We propose an integrated method of data-driven and mechanism models for well logging formation evaluation,explicitly focusing on predicting reservoir parameters,such as porosity and water saturation.Accurately interpr...We propose an integrated method of data-driven and mechanism models for well logging formation evaluation,explicitly focusing on predicting reservoir parameters,such as porosity and water saturation.Accurately interpreting these parameters is crucial for effectively exploring and developing oil and gas.However,with the increasing complexity of geological conditions in this industry,there is a growing demand for improved accuracy in reservoir parameter prediction,leading to higher costs associated with manual interpretation.The conventional logging interpretation methods rely on empirical relationships between logging data and reservoir parameters,which suffer from low interpretation efficiency,intense subjectivity,and suitability for ideal conditions.The application of artificial intelligence in the interpretation of logging data provides a new solution to the problems existing in traditional methods.It is expected to improve the accuracy and efficiency of the interpretation.If large and high-quality datasets exist,data-driven models can reveal relationships of arbitrary complexity.Nevertheless,constructing sufficiently large logging datasets with reliable labels remains challenging,making it difficult to apply data-driven models effectively in logging data interpretation.Furthermore,data-driven models often act as“black boxes”without explaining their predictions or ensuring compliance with primary physical constraints.This paper proposes a machine learning method with strong physical constraints by integrating mechanism and data-driven models.Prior knowledge of logging data interpretation is embedded into machine learning regarding network structure,loss function,and optimization algorithm.We employ the Physically Informed Auto-Encoder(PIAE)to predict porosity and water saturation,which can be trained without labeled reservoir parameters using self-supervised learning techniques.This approach effectively achieves automated interpretation and facilitates generalization across diverse datasets.展开更多
With the increase of international trade activities and the gradual melting of the polar ice cap,the importance of the Arctic route for marine transportation has been emphasized.Prediction of the polar navigation wind...With the increase of international trade activities and the gradual melting of the polar ice cap,the importance of the Arctic route for marine transportation has been emphasized.Prediction of the polar navigation window period is crucial for navigating in the Arctic route,which is of great significance to the selection of the route and the optimization of navigation.This paper introduces the establishment of a risk index system,determination of risk index weight,establishment of a risk evaluation model,and prediction algorithm for the window period.In addition,data sources of both environmental factors and ship factors are introducted,and their shortcomings are analyzed,followed by introduction of various methods involved in window prediction and analysis of their advantages and disadvantages.The quantitative risk evaluation and window period algorithm can provide a reference for the research of polar navigation window period prediction.展开更多
To scientifically evaluate the restoration performance of ancient city walls,Terahertz time-domain spectroscopy(THz-TDS)and infrared thermal imaging technology were applied to assess the Desheng Fortress(Ming Dynasty)...To scientifically evaluate the restoration performance of ancient city walls,Terahertz time-domain spectroscopy(THz-TDS)and infrared thermal imaging technology were applied to assess the Desheng Fortress(Ming Dynasty).Three representative sections were examined:adobe brick masonry repaired(Area 1),well-preserved original(Area 2),and layer-by-layer ramming repaired(Area 3).THz spectral data revealed significant differences between Area 1(time delay:3.72 ps;refractive index:2.224)and Area 2(time delay:3.02 ps;refractive index:2.107),while Area 3(time delay:3.12 ps;refractive index:2.098)demonstrated nearly identical THz spectral data to Area 2.Infrared thermal imaging also showed that the Area 3 restored by layer-by-layer ramming exhibited greater uniformity with fewer instances of cracks,capillary phenomena,or biological diseases.The proposed point-surface integrated evaluation methodology synergistically combines infrared thermography mapping of heritage surfaces with THz spectral datasets acquired through in-situ micro-sampling,enabling quantitative restoration assessment and providing a novel approach for scientifically validating traditional conservation techniques.展开更多
Background:Rosa chinensis Jacq.and Rosa rugosa Thunb.are not only of ornamental value,but also edible flowers and the flower buds have been listed in the Chinese Pharmacopoeia as traditional medicines.The two plants h...Background:Rosa chinensis Jacq.and Rosa rugosa Thunb.are not only of ornamental value,but also edible flowers and the flower buds have been listed in the Chinese Pharmacopoeia as traditional medicines.The two plants have some differences in efficacy,but the flower buds are easily confused for similar traits.In addition,large-scale cultivation of ornamental rose flowers may lead to a decrease in the effective components of medicinal roses.Therefore,it is necessary to study the chemical composition and make quality evaluation of Rosae Chinensis Flos(Yueji)and Rosae Rugosae Flos(Meigui).Methods:In this study,40 batches of samples including Meigui and Yueji from different regions in China were collected to establish high-performance liquid chromatography fingerprints.Then,the fingerprints data was analyzed using principal component analysis,hierarchical cluster analysis,and partial least squares discriminant analysis analysis chemometrics to obtain information on intergroup differences,and non-targeted metabolomic techniques were applied to identify and compare chemical compositions of samples which were chosen from groups with large differences.Differential compounds were screened by orthogonal partial least-squares discriminant analysis and S-plot,and finally multi-component quantification was performed to comprehensively evaluate the quality of Yueji and Meigui.Results:The similarity between the fingerprints of 40 batches roses and the reference print R was 0.73 to 0.93,indicating that there were similarities and differences between the samples.Through principal component analysis and hierarchical cluster analysis of fingerprints data,the samples from different origins and varieties were intuitively divided into four groups.Partial least-squares discriminant analysis analysis showed that Meigui and Yueji cluster into two categories and the model was reliable.A total of 89 compounds were identified by high resolution mass spectrometry,mainly were flavonoids and flavonoid glycosides,as well as phenolic acids.Eight differential components were screened out by orthogonal partial least-squares discriminant analysis and S-plot analysis.Quantitative analyses of the eight compounds,including gallic acid,ellagic acid,hyperoside,isoquercitrin,etc.,showed that Yueji was generally richer in phenolic acids and flavonoids than Meigui,and the quality of Yueji from Shandong and Hebei was better.It is worth noting that Xinjiang rose is rich in various components,which is worth focusing on more in-depth research.Conclusion:In this study,the fingerprints of Meigui and Yueji were established.The chemical components information of roses was further improved based on non-targeted metabolomics and mass spectrometry technology.At the same time,eight differential components of Meigui and Yueji were screened out and quantitatively analyzed.The research results provided a scientific basis for the quality control and rational development and utilization of Rosae Chinensis Flos and Rosae Rugosae Flos,and also laid a foundation for the study of their pharmacodynamic material basis.展开更多
Introduction: The WHO’s measles control strategy is based on epidemiological surveillance and vaccination. Little is currently known about the performance of the surveillance system, particularly in outlying areas. I...Introduction: The WHO’s measles control strategy is based on epidemiological surveillance and vaccination. Little is currently known about the performance of the surveillance system, particularly in outlying areas. It is in this context that the present study was carried out to evaluate the measles epidemiological surveillance system in the Kangaba health district. Method: This was a descriptive cross-sectional study with retrospective data collection for the period from 1 January to 31 December 2022 in the Kangaba health district with 18 epidemiological surveillance officers. Data were collected using an observation grid and documentary analysis. Results: We found a simplicity of 97%, a representativeness of 95% and a reactivity of 53%. Not all notified cases were sampled (64%). Of the 17 CSCom, 8 were positive. A total of 34 confirmed cases of measles were recorded, with one death. Conclusion: Overall, the system is functional and well-established in the health centres, but it remains important to ensure that suspected cases are investigated and that the time between sampling and the availability of laboratory results is respected.展开更多
基金the National Key Research and Development Program of China(2023YFE0197800)the Natural Sciences and Engineering Research Council of Canada(NSERC)through the CREATE-oN DuTy!Program(496439-2017)+5 种基金the Canada Research Chair in Multi-polar Infrared Vision(MIVIM)the Canada Foundation for Innovationthe Natural Sciences and Engineering Research Council(NSERC)Discovery Grants Program(RGPIN-2020-04595)the Canada Foundation for Innovation(CFI)Research Chairs Program(950-230876)the New Frontiers in Research Fund—Exploration(NFRFE-2019-00647)the CFI-JELF program(38794)。
文摘Infrared thermography has been widely applied in real industrial inspection of aerospace,energy management systems,engines,and electric systems.However,two-dimensional imaging modality limits its development.Here,a technique named frequency multiplexed photothermal correlation tomography(FM-PCT)was developed to enable non-destructive and contactless cross-sectional imaging for manufactured material evaluation and characterization.By combining advantages of photothermal tomography and pulsed thermography,FM-PCT facilitates the generation of three-dimensional thermal images through temporal superposition(stacking)of two-dimensional images from sequential subsurface depths.FM-PCT image processing involves pulsed excitation signals to which frequency delay and matched filtering techniques are applied.Major features of FM-PCT are high-resolution three-dimensional tomographic imaging under low camera frame-rate conditions with self-correcting capability for diffusion(blurring)correction of subsurface images due to cross-correlation processing of individual frequencies in the Fourier decomposition spectrum of the excitation pulse.Furthermore,FM-PCT extends truncated-correlation photothermal coherence tomography from chirp and pulsed signals to more general linear heating sources.Lock-in thermography and x-ray computed tomography validation demonstrate that 3D FM-PCT imaging accurately reveals subsurface discontinuities/defects in solids despite the diffusive nature of thermal-wave imaging.
文摘In recent years, advanced composite structures are used extensively in many industries such as aerospace, aircraft, automobile, pipeline and civil engineering. Reliability and safety are crucial requirements posed by them to the advanced composite structures be- cause of their harsh working conditions. Therefore, as a very important measure, structural health monitoring （SHM） in-service is deft- nitely demanded for ensuring their safe working in-situ. In this paper, fiber Bragg grating （FBG） sensors are surface-mounted on the hoop and in the axial directions of a FRP pressure vessel to monitor the strain status during its pressurization. The experimental results show that the FBG sensors could be used to monitor the strain development and determine the ultimate failure strain of the composite pressure vessel.
基金Sichuan province Science and Technology department( No. 2011GZ0002 and No. 2013HH0059)the university basic scientific research project( No. ZYGX2013J090 ) for funding the work
文摘This paper introduces recent research work in the field of pulsed electromagnetic non-destructive testing/evaluation.These are pulsed eddy current,pulsed magnetic flux leakage and eddy current pulsed thermography.This paper introduces pulsed electromagnetic techniques and their different case studies on defect detection as well as stress characterisation.Experimental tests have been validated and future research plans are discussed.This paper demonstrates pulsed electromagnetic non-destructive testing and evaluation for not only depth information,but also for multiple parameter measurement and multiple integration,which are important for future development.
文摘This article should not be considered as a full review of current methods for non-destructive testing of surface layers. Rather, it is a subjective in this area. However, the article provides some review of the challenges posed by the current state of surface layers treatment techniques on the area of Non-Destructive materials evaluation: enhancement of the sensitivity to the type of defects, increasing resolution to submicron values, the requirement to diagnose the surface layers with depth resolution of properties, diagnosis of multilayer multicomponent surface layers and coatings, treated with concentrated energy.
基金supported by the National Key Research and Development Program of China (No. 2016YFC0701102)the National Nature Science Foundation of China(No.51538003)the Shenzhen Technology Innovation Program (No.JSGG20150330103937411)
文摘Non-destructive measurement of absolute stress in steel members can provide useful information to optimize the design of steel structures and allow the safety of existing structures to be evaluated.This paper investigates the non-destructive capability of ultrasonic shear-wave spectroscopy in absolute stress evaluation of steel members.The effect of steel-member stress on the shear-wave amplitude spectrum is investigated,and a method of absolute stress measurement is proposed.Specifically,the process for evaluating absolute stress using shear-wave spectroscopy is summarized.Two steel members are employed to investigate the relationship between the stress and the frequency in shear-wave echo amplitude spectrum.The H-beam loaded by the universal testing machine is evaluated by the proposed method and the traditional strain gauge method for verification.The results show that the proposed method is effective and accurate for determining absolute stress in steel members.
基金supported by the National Natural Science Foundation of China(Grant No.52275512).
文摘Composite materials are increasingly used in the aerospace and automotive industries due to their high strength-toweight ratio and fatigue resistance.These structures may develop internal defects during manufacturing or service,compromising their integrity and safety.Thus,non-destructive defect detection is critical during production to ensure safety and reliability.This study explores the application of terahertz time-domain spectroscopy(THz-TDS)for detecting damage in different glass fiber-reinforced polymer(GFRP)manufacturing processes.A cross-correlation-based impulse response function extraction algorithm and image enhancement method are proposed.The method targets both deep and minor defects in GFRP,leveraging the correlation between the terahertz reference signal and the time-domain detection signal to extract the terahertz impulse response function via a one-dimensional iterative deconvolution algorithm.Testing on samples with pre-fabricated delamination,three-point bending damage,and drilled damage demonstrated the method’s efficacy in extracting impulse response functions of delamination defects,which aids in defect localization and improved image representation.In the THz imaging analysis of GFRP manufacturing process damage,signal alignment,windowing,and morphology positioning techniques were applied based on the extracted impulse response functions.The proposed method significantly improved the quality of THz images for defect detection in GFRP,as demonstrated by objective evaluations and comparisons.These advancements provide a robust and effective tool for the non-destructive evaluation of composite materials.
文摘Longitudinal joint construction quality is critical to the life of flexible pavements.Maintaining deteriorated longitudinal joints has become a challenge for many highway agencies.Improving the joint's quality through better compaction during construction can help achieve flexible pavements with longer service lives and less maintenance.Current quality control(QC)and quality assurance(QA)plans provide limited coverage.Consequently,the risk of missing areas with poor joint compaction is significant.A density profiling system(DPS)is a non-destructive alternative to conventional destructive evaluation methods.It can provide quick and continuous real-time coverage of the compaction during construction in dielectrics.The paper presents several case studies comparing various types of longitudinal joints and demonstrating the use of DPS to evaluate the joint's compaction quality.The paper shows that dielectric measurements can provide valuable insight into the ability of various construction techniques to achieve adequate levels of compaction at the longitudinal joint.The paper proposes a dielectric-based longitudinal joint quality index(LJQI)to evaluate the relative compaction of the joint during construction.It also shows that adopting DPS for assessing the compaction of longitudinal joints can minimize the risk of agencies accepting poorly constructed joints,identify locations of poor quality during construction,and achieve better-performing flexible pavements.
基金Ministry of Higher Education of Malaysia for funding the project on PEC NDT at IIUM through the research grant FRGS16-059-0558supported by the National Natural Science Foundation of China under research grants 51677187 and 51307172
文摘Pulsed eddy current （PEC） non-destructive test- ing and evaluation （NDT＆E） has been around for some time and it is still attracting extensive attention from researchers around the globe, which can be witnessed through the reports reviewed in this paper. Thanks to its richness of spectral components, various applications of this technique have been proposed and reported in the lit- erature covering both structural integrity inspection and material characterization in various industrial sectors. To support its development and for better understanding of the phenomena around the transient induced eddy currents, attempts for its modelling both analytically and numeri- cally have been made by researchers around the world. This review is an attempt to capture the state-of-the-art development and applications of PEC, especially in the last 15 years and it is not intended to be exhaustive. Future challenges and opportunities for PEC NDT＆E are also presented.
基金supported by the UK EPSRC Platform Grant:Through-life performance:From science to instrumentation(Grant No.EP/P027121/1).
文摘Although machine Learning has demonstrated exceptional applicability in thermographic inspection,precise defect reconstruction is still challenging,especially for complex defect profiles with limited defect sample diversity.Thus,this paper proposes a self-enhancement defect reconstruction technique based on cycle-consistent generative adversarial network(Cycle-GAN)that accurately characterises complex defect profiles and generates reliable artificial thermal images for dataset augmentation,enhancing defect characterisation.By using a synthetic dataset from simulation and experiments,the network overcomes the limited samples problem by learning the diversity of complex defects from finite element modelling and obtaining the thermography uncertainty patterns from practical experiments.Then,an iterative strategy with a self-enhancement capability optimises the characterisation accuracy and data generation performance.The designed loss function structure with cycle consistency and identity loss constrains the GAN’s transfer variation to guarantee augmented data quality and defect reconstruction accuracy simultaneously,while the self-enhancement results significantly improve accuracy in thermal images and defect profile reconstruction.The experimental results demonstrate the feasibility of the proposed method by attaining high accuracy with optimal loss norm for defect profile reconstruction with a Recall score over 0.92.The scalability investigation of different materials and defect types is also discussed,highlighting its capability for diverse thermography quantification and automated inspection scenarios.
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.
文摘BACKGROUND Coronavirus disease 2019(COVID-19)disrupted healthcare and led to increased telehealth use.We explored the impact of COVID-19 on liver transplant evaluation(LTE).AIM To understand the impact of telehealth on LTE during COVID-19 and to identify disparities in outcomes disaggregated by sociodemographic factors.METHODS This was a retrospective study of patients who initiated LTE at our center from 3/16/20-3/16/21(“COVID-19 era”)and the year prior(3/16/19-3/15/20,“pre-COVID-19 era”).We compared LTE duration times between eras and explored the effects of telehealth and inpatient evaluations on LTE duration,listing,and pretransplant mortality.RESULTS One hundred and seventy-eight patients were included in the pre-COVID-19 era cohort and one hundred and ninety-nine in the COVID-19 era cohort.Twentynine percent(58/199)of COVID-19 era initial LTE were telehealth,compared to 0%(0/178)pre-COVID-19.There were more inpatient evaluations during COVID-19 era(40%vs 28%,P<0.01).Among outpatient encounters,telehealth use for initial LTE during COVID-19 era did not impact likelihood of listing,pretransplant mortality,or time to LTE and listing.Median times to LTE and listing during COVID-19 were shorter than pre-COVID-19,driven by increased inpatient evaluations.Sociodemographic factors were not predictive of telehealth.CONCLUSION COVID-19 demonstrates a shift to telehealth and inpatient LTE.Telehealth does not impact LTE or listing duration,likelihood of listing,or mortality,suggesting telehealth may facilitate LTE without negative outcomes.
基金the National Key Research Program of China under granted No.92164201National Natural Science Foundation of China for Distinguished Young Scholars No.62325403+2 种基金Natural Science Foundation of Jiangsu Province(BK20230498)Jiangsu Funding Program for Excellent Postdoctoral Talent(2024ZB427)the National Natural Science Foundation of China(62304147).
文摘Solid-state batteries are widely recognized as the next-generation energy storage devices with high specific energy,high safety,and high environmental adaptability.However,the research and development of solid-state batteries are resource-intensive and time-consuming due to their complex chemical environment,rendering performance prediction arduous and delaying large-scale industrialization.Artificial intelligence serves as an accelerator for solid-state battery development by enabling efficient material screening and performance prediction.This review will systematically examine how the latest progress in using machine learning(ML)algorithms can be used to mine extensive material databases and accelerate the discovery of high-performance cathode,anode,and electrolyte materials suitable for solid-state batteries.Furthermore,the use of ML technology to accurately estimate and predict key performance indicators in the solid-state battery management system will be discussed,among which are state of charge,state of health,remaining useful life,and battery capacity.Finally,we will summarize the main challenges encountered in the current research,such as data quality issues and poor code portability,and propose possible solutions and development paths.These will provide clear guidance for future research and technological reiteration.
基金supported by the National Natural Science Foundation of China for Distinguished Young Scholars(Grant No.42225206)National Natural Science Foundation of China(42207180,42477209,42302320).
文摘Subgrade engineering is a fundamental aspect of infrastructure construction in China.As the primary structural element responsible for bearing and distributing traffic loads,the subgrade must not only withstand the substantial pressures exerted by vehicles,trains,and other forms of transportation,but also efficiently transfer these loads to the underlying foundation,ensuring the stability and longevity of the roadway.In recent years,advancements in subgrade engineering technology have propelled the industry towards smarter,greener,and more sustainable practices,particularly in the areas of intelligent monitoring,disaster management,and innovative construction methods.This paper reviews the application and methodologies of intelligent testing equipment,including cone penetration testing(CPT)devices,soil resistivity testers,and intelligent rebound testers,in subgrade engineering.It examines the operating principles,advantages,limitations,and application ranges of these tools in subgrade testing.Additionally,the paper evaluates the practical use of advanced equipment from both domestic and international perspectives,addressing the challenges encountered by various instruments in realworld applications.These devices enable precise,comprehensive testing and evaluation of subgrade conditions at different stages,providing real-time data analysis and intelligent early warnings.This supports effective subgrade health management and maintenance.As intelligent technologies continue to evolve and integrate,these tools will increasingly enhance the accuracy,efficiency,and sustainability of subgrade monitoring.
基金Supported by PetroChina Prospective and Basic Technological Project(2022DJ5503).
文摘China has abundant resources of hot dry rocks.However,due to the fact that the evaluation methods for favorable areas are mainly qualitative,and the evaluation indicators and standards are inconsistent,which restrict the evaluation efficiency and exploration process of dry hot rocks.This paper is based on the understanding of the geologic features and genesis mechanisms of hot dry rocks in China and abroad.By integrating the main controlling factors of hot dry rock formation,and using index grading and quantification,the fuzzy hierarchical comprehensive method is applied to establish an evaluation system and standards for favorable areas of hot dry rocks.The evaluation system is based on four indicators:heat source,thermal channel,thermal reservoir and cap rock.It includes 11 evaluation parameters,including time of magmatic/volcanic activity,depth of molten mass or magma chamber,distribution of discordogenic faults,burial depth of thermal reservoir,cap rock type and thickness,surface thermal anomaly,heat flow,geothermal gradient,Moho depth,Curie depth,Earthquake magnitude and focal depth.Each parameter is divided into 3 levels.Applying this evaluation system to assess hot dry rock in central Inner Mongolia revealed that Class I favorable zones cover approximately 494 km^(2),while Class II favorable zones span about 5.7×10^(4) km^(2).The Jirgalangtu Sag and Honghaershute Sag in the Erlian Basin,along with Reshuitang Town in Keshiketeng Banner,Reshui Town in Ningcheng County,and Reshuitang Town in Aohan Banner of Chifeng City,are identified as Class I favorable zones for hot dry rock resources.These areas are characterized by high-temperature subsurface molten bodies or magma chambers serving as high-quality heat sources,shallow thermal reservoir depths,and overlying thick sedimentary rock layers acting as caprock.The establishment and application of the evaluation system for favorable areas of hot dry rock are expected to provide new approaches and scientific basis for guiding the practice of selecting hot dry rock areas in China.
基金Supported by the National Key Research and Development Project,Clinical Study on the Treatment of Refractory Membranous Nephropathy with the Treatment of Strengthening Spleen and Draining Dampness in Method using Single Group Target Value Method(No.2019YFC1709403)Systematic Study on the Diagnosis and Treatment Rules of Membranous Nephropathy in Traditional Chinese Medicine(No.2023YFC35033501,No.2023YFC35033503)。
文摘OBJECTIVE:To evaluate the 10-year therapeutic efficacy of Traditional Chinese Medicine(TCM)using the Strengthening Spleen and Draining Dampness therapy in the management of idiopathic membranous nephropathy(IMN).METHODS:A single-center,retrospective analysis was conducted on patients diagnosed with IMN who met predefined inclusion and exclusion criteria.Data were collected from the Department of Nephrology at Longhua Hospital,affiliated with Shanghai University of Traditional Chinese Medicine,between January 2007 and December 2011.Clinical parameters including 24-h urinary protein,serum albumin,serum creatinine,and estimated glomerular filtration rate(e GFR,EPI)were assessed at baseline and at 1,3,5,and 10 years of follow-up.The efficacy of the Strengthening Spleen and Draining Dampness therapy was analyzed using repeated measures analysis of variance(ANOVA).Kaplan-Meier survival curves and multivariate proportional hazards model(Cox regression models)were employed to identify factors associated with treatment outcomes.RESULTS:A total of 265 patients were included,with a median follow-up duration of 96 months(36,122).TCM treatment significantly reduced 24-h urinary protein levels(P<0.001),and increased serum albumin levels(P<0.001),while serum creatinine remained stable(P=0.187).Remission rates at 1,3,5,and 10 years were 52.81%,69.71%,68.39%,and 72.36%,respectively,and the rates of avoiding composite outcome events at the same intervals were 98.27%,94.29%,94.19%,and 93.50%.In the subgroup receiving TCM only,remission rates were 56.67%,84.44%,76.32%,and 82.86%.For patients treated initially with Western Medicine followed by TCM,the rates were 52.83%,65.85%,67.47%and 67.75%.In the cohort of patients who received TCM as their first-line therapy,remission rates were 49.23%,62.50%,61.76%,and 69.23%.Multivariate Cox regression analysis revealed that the duration of TCM treatment[hazard ratio(HR)=0.826,95%confidence interval(CI)(0.779,0.876),P<0.001],presence of hypertension[HR=1.912,95%CI(1.181,3.094),P=0.008],baseline serum albumin level[HR=0.930,95%CI(0.894,0.969),P<0.001],and the rate of serum albumin increase within the first year of treatment[HR=0.930,95%CI(0.909,0.957),P<0.001]were significantly associated with clinical outcomes.CONCLUSION:The Strengthening Spleen and Draining Dampness therapy demonstrated robust short-and longterm efficacy in treating IMN,with high rates of remission and renal survival over 10 years.Key factors influencing clinical remission included the duration of TCM treatment,baseline serum albumin levels,the presence of hypertension,and the rate of increase in serum albumin within the first year.These findings suggest that this TCM approach provides a viable long-term treatment option for IMN.
基金supported by National Key Research and Development Program (2019YFA0708301)National Natural Science Foundation of China (51974337)+2 种基金the Strategic Cooperation Projects of CNPC and CUPB (ZLZX2020-03)Science and Technology Innovation Fund of CNPC (2021DQ02-0403)Open Fund of Petroleum Exploration and Development Research Institute of CNPC (2022-KFKT-09)
文摘We propose an integrated method of data-driven and mechanism models for well logging formation evaluation,explicitly focusing on predicting reservoir parameters,such as porosity and water saturation.Accurately interpreting these parameters is crucial for effectively exploring and developing oil and gas.However,with the increasing complexity of geological conditions in this industry,there is a growing demand for improved accuracy in reservoir parameter prediction,leading to higher costs associated with manual interpretation.The conventional logging interpretation methods rely on empirical relationships between logging data and reservoir parameters,which suffer from low interpretation efficiency,intense subjectivity,and suitability for ideal conditions.The application of artificial intelligence in the interpretation of logging data provides a new solution to the problems existing in traditional methods.It is expected to improve the accuracy and efficiency of the interpretation.If large and high-quality datasets exist,data-driven models can reveal relationships of arbitrary complexity.Nevertheless,constructing sufficiently large logging datasets with reliable labels remains challenging,making it difficult to apply data-driven models effectively in logging data interpretation.Furthermore,data-driven models often act as“black boxes”without explaining their predictions or ensuring compliance with primary physical constraints.This paper proposes a machine learning method with strong physical constraints by integrating mechanism and data-driven models.Prior knowledge of logging data interpretation is embedded into machine learning regarding network structure,loss function,and optimization algorithm.We employ the Physically Informed Auto-Encoder(PIAE)to predict porosity and water saturation,which can be trained without labeled reservoir parameters using self-supervised learning techniques.This approach effectively achieves automated interpretation and facilitates generalization across diverse datasets.
文摘With the increase of international trade activities and the gradual melting of the polar ice cap,the importance of the Arctic route for marine transportation has been emphasized.Prediction of the polar navigation window period is crucial for navigating in the Arctic route,which is of great significance to the selection of the route and the optimization of navigation.This paper introduces the establishment of a risk index system,determination of risk index weight,establishment of a risk evaluation model,and prediction algorithm for the window period.In addition,data sources of both environmental factors and ship factors are introducted,and their shortcomings are analyzed,followed by introduction of various methods involved in window prediction and analysis of their advantages and disadvantages.The quantitative risk evaluation and window period algorithm can provide a reference for the research of polar navigation window period prediction.
文摘To scientifically evaluate the restoration performance of ancient city walls,Terahertz time-domain spectroscopy(THz-TDS)and infrared thermal imaging technology were applied to assess the Desheng Fortress(Ming Dynasty).Three representative sections were examined:adobe brick masonry repaired(Area 1),well-preserved original(Area 2),and layer-by-layer ramming repaired(Area 3).THz spectral data revealed significant differences between Area 1(time delay:3.72 ps;refractive index:2.224)and Area 2(time delay:3.02 ps;refractive index:2.107),while Area 3(time delay:3.12 ps;refractive index:2.098)demonstrated nearly identical THz spectral data to Area 2.Infrared thermal imaging also showed that the Area 3 restored by layer-by-layer ramming exhibited greater uniformity with fewer instances of cracks,capillary phenomena,or biological diseases.The proposed point-surface integrated evaluation methodology synergistically combines infrared thermography mapping of heritage surfaces with THz spectral datasets acquired through in-situ micro-sampling,enabling quantitative restoration assessment and providing a novel approach for scientifically validating traditional conservation techniques.
基金supported by the key project at the central government level:The ability establishment of sustainable use for valuable Chinese medicine resources(Grant number 2060302)the National Natural Science Foundation of China(Grant number 82373982,82173929).
文摘Background:Rosa chinensis Jacq.and Rosa rugosa Thunb.are not only of ornamental value,but also edible flowers and the flower buds have been listed in the Chinese Pharmacopoeia as traditional medicines.The two plants have some differences in efficacy,but the flower buds are easily confused for similar traits.In addition,large-scale cultivation of ornamental rose flowers may lead to a decrease in the effective components of medicinal roses.Therefore,it is necessary to study the chemical composition and make quality evaluation of Rosae Chinensis Flos(Yueji)and Rosae Rugosae Flos(Meigui).Methods:In this study,40 batches of samples including Meigui and Yueji from different regions in China were collected to establish high-performance liquid chromatography fingerprints.Then,the fingerprints data was analyzed using principal component analysis,hierarchical cluster analysis,and partial least squares discriminant analysis analysis chemometrics to obtain information on intergroup differences,and non-targeted metabolomic techniques were applied to identify and compare chemical compositions of samples which were chosen from groups with large differences.Differential compounds were screened by orthogonal partial least-squares discriminant analysis and S-plot,and finally multi-component quantification was performed to comprehensively evaluate the quality of Yueji and Meigui.Results:The similarity between the fingerprints of 40 batches roses and the reference print R was 0.73 to 0.93,indicating that there were similarities and differences between the samples.Through principal component analysis and hierarchical cluster analysis of fingerprints data,the samples from different origins and varieties were intuitively divided into four groups.Partial least-squares discriminant analysis analysis showed that Meigui and Yueji cluster into two categories and the model was reliable.A total of 89 compounds were identified by high resolution mass spectrometry,mainly were flavonoids and flavonoid glycosides,as well as phenolic acids.Eight differential components were screened out by orthogonal partial least-squares discriminant analysis and S-plot analysis.Quantitative analyses of the eight compounds,including gallic acid,ellagic acid,hyperoside,isoquercitrin,etc.,showed that Yueji was generally richer in phenolic acids and flavonoids than Meigui,and the quality of Yueji from Shandong and Hebei was better.It is worth noting that Xinjiang rose is rich in various components,which is worth focusing on more in-depth research.Conclusion:In this study,the fingerprints of Meigui and Yueji were established.The chemical components information of roses was further improved based on non-targeted metabolomics and mass spectrometry technology.At the same time,eight differential components of Meigui and Yueji were screened out and quantitatively analyzed.The research results provided a scientific basis for the quality control and rational development and utilization of Rosae Chinensis Flos and Rosae Rugosae Flos,and also laid a foundation for the study of their pharmacodynamic material basis.
文摘Introduction: The WHO’s measles control strategy is based on epidemiological surveillance and vaccination. Little is currently known about the performance of the surveillance system, particularly in outlying areas. It is in this context that the present study was carried out to evaluate the measles epidemiological surveillance system in the Kangaba health district. Method: This was a descriptive cross-sectional study with retrospective data collection for the period from 1 January to 31 December 2022 in the Kangaba health district with 18 epidemiological surveillance officers. Data were collected using an observation grid and documentary analysis. Results: We found a simplicity of 97%, a representativeness of 95% and a reactivity of 53%. Not all notified cases were sampled (64%). Of the 17 CSCom, 8 were positive. A total of 34 confirmed cases of measles were recorded, with one death. Conclusion: Overall, the system is functional and well-established in the health centres, but it remains important to ensure that suspected cases are investigated and that the time between sampling and the availability of laboratory results is respected.
