Industrial data mining usually deals with data from different sources.These heterogeneous datasets describe the same object in different views.However,samples from some of the datasets may be lost.Then the remaining s...Industrial data mining usually deals with data from different sources.These heterogeneous datasets describe the same object in different views.However,samples from some of the datasets may be lost.Then the remaining samples do not correspond one-to-one correctly.Mismatched datasets caused by missing samples make the industrial data unavailable for further machine learning.In order to align the mismatched samples,this article presents a cooperative iteration matching method(CIMM)based on the modified dynamic time warping(DTW).The proposed method regards the sequentially accumulated industrial data as the time series.Mismatched samples are aligned by the DTW.In addition,dynamic constraints are applied to the warping distance of the DTW process to make the alignment more efficient.Then a series of models are trained with the cumulated samples iteratively.Several groups of numerical experiments on different missing patterns and missing locations are designed and analyzed to prove the effectiveness and the applicability of the proposed method.展开更多
Geological samples often contain significant amounts of iron,which,although not typically the target element,can substantially interfere with the analysis of other elements of interest.To mitigate these interferences,...Geological samples often contain significant amounts of iron,which,although not typically the target element,can substantially interfere with the analysis of other elements of interest.To mitigate these interferences,amidoximebased radiation grafted adsorbents have been identified as effective for iron removal.In this study,an amidoximefunctionalized,radiation-grafted adsorbent synthesized from polypropylene waste(PPw-g-AO-10)was employed to remove iron from leached geological samples.The adsorption process was systematically optimized by investigating the effects of pH,contact time,adsorbent dosage,and initial ferric ion concentration.Under optimal conditions-pH1.4,a contact time of 90 min,and an initial ferric ion concentration of 4500 mg/L-the adsorbent exhibited a maximum iron adsorption capacity of 269.02 mg/g.After optimizing the critical adsorption parameters,the adsorbent was applied to the leached geological samples,achieving a 91%removal of the iron content.The adsorbent was regenerated through two consecutive cycles using 0.2 N HNO_(3),achieving a regeneration efficiency of 65%.These findings confirm the efficacy of the synthesized PPw-g-AO-10 as a cost-effective and eco-friendly adsorbent for successfully removing iron from leached geological matrices while maintaining a reasonable degree of reusability.展开更多
Flow cytometry(FCM),characterized by its simplicity,rapid processing,multiparameter analysis,and high sen-sitivity,is widely used in the diagnosis,treatment,and prognosis of hematological malignancies.FCM testing of t...Flow cytometry(FCM),characterized by its simplicity,rapid processing,multiparameter analysis,and high sen-sitivity,is widely used in the diagnosis,treatment,and prognosis of hematological malignancies.FCM testing of tissue samples not only aids in diagnosing and classifying hematological cancers,but also enables the detection of solid tumors.Its ability to detect numerous marker parameters from small samples is particularly useful when dealing with limited cell quantities,such as in fine-needle biopsy samples.This attribute not only addresses the challenge posed by small sample sizes,but also boosts the sensitivity of tumor cell detection.The significance of FCM in clinical and pathological applications continues to grow.To standardize the use of FCM in detecting hematological malignant cells in tissue samples and to improve quality control during the detection process,experts from the Cell Analysis Professional Committee of the Chinese Society of Biotechnology jointly drafted and agreed upon this consensus.This consensus was formulated based on current literature and clinical practices of all experts across clinical,laboratory,and pathological fields in China.It outlines a comprehensive workflow of FCM-based assay for the detection of hematological malignancies in tissue samples,including report content,interpretation,quality control,and key considerations.Additionally,it provides recommendations on antibody panel designs and analytical approaches to enhancing FCM tests,particularly in cases with limited sample sizes.展开更多
Three-dimensional printing(3DP)offers valuable insight into the characterization of natural rocks and the verification of theoretical models due to its high reproducibility and accurate replication of complex defects ...Three-dimensional printing(3DP)offers valuable insight into the characterization of natural rocks and the verification of theoretical models due to its high reproducibility and accurate replication of complex defects such as cracks and pores.In this study,3DP gypsum samples with different printing directions were subjected to a series of uniaxial compression tests with in situ micro-computed tomography(micro-CT)scanning to quantitatively investigate their mechanical anisotropic properties and damage evolution characteristics.Based on the two-dimensional(2D)CT images obtained at different scanning steps,a novel void ratio variable was derived using the mean value and variance of CT intensity.Additionally,a constitutive model was formulated incorporating the proposed damage variable,utilizing the void ratio variable.The crack evolution and crack morphology of 3DP gypsum samples were obtained and analyzed using the 3D models reconstructed from the CT images.The results indicate that 3DP gypsum samples exhibit mechanical anisotropic characteristics similar to those found in naturally sedimentary rocks.The mechanical anisotropy is attributed to the bedding planes formed between adjacent layers and pillar-like structures along the printing direction formed by CaSO_(4)·2H_(2)O crystals of needle-like morphology.The mean gray intensity of the voids has a positive linear relationship with the threshold value,while the CT variance and void ratio have concave and convex relationships,respectively.The constitutive model can effectively match the stress–strain curves obtained from uniaxial compression experiments.This study provides comprehensive explanations of the failure modes and anisotropic mechanisms of 3DP gypsum samples,which is important for characterizing and understanding the failure mechanism and microstructural evolution of 3DP rocks when modeling natural rock behavior.展开更多
The investigation of whether sediment samples contain representative grain size distribution information is important for the accurate extraction of sediment characteristics and conduct of related sedimentary record s...The investigation of whether sediment samples contain representative grain size distribution information is important for the accurate extraction of sediment characteristics and conduct of related sedimentary record studies.This study comparatively analyzed the numerical and qualitative differences and the degree of correlation of 36 sets of the characteristic parameters of surface sediment parallel sample grain size distribution from three sampling profiles at Jinsha Bay Beach in Zhanjiang,western Guangdong.At each sampling point,five parallel subsamples were established at intervals of 0,10,20,50,and 100 cm along the coastline.The research findings indicate the following:1)relatively large differences in the mean values of the different parallel samples(0.19–0.34Φ),with smaller differences observed in other characteristic grain sizes(D_(10),D_(50),and D_(90));2)small differences in characteristic values among various parallel sample grain size parameters,with at least 33%of the combinations of qualitative results showing inconsistency;3)50%of the regression equations between the skewness of different parallel samples displaying no significant correlation;4)relative deviations of−47.91%to 27.63%and−49.20%to 2.08%existing between the particle size parameters of a single sample and parallel samples(with the average obtained)at intervals of 10 and 50 cm,respectively.As such,small spatial differences,even within 100 cm,can considerably affect grain size parameters.Given the uncertain reasons underlying the representativeness of the samples,which may only cover the area immediately surrounding the sampling station,researchers are advised to design parallel sample collection strategies based on the spatiotemporal distribution characteristics of the parameters of interest during sediment sample collection.This study provides a typical case of the comparative analysis of parallel sample grain size parameters,with a focus on small spatial beach sediment,which contributes to the enhanced understanding of the accuracy and reliability of sediment sample collection strategies and extraction of grain size information.展开更多
The exploration of asteroids has received increasing attention since the 1990s because of the unique information these objects contain about the history of the early solar system.Quasi-satellites are a population of a...The exploration of asteroids has received increasing attention since the 1990s because of the unique information these objects contain about the history of the early solar system.Quasi-satellites are a population of asteroids that co-orbit closely with,but are outside the gravitational control of,the planet.So far,only five Earth quasi-satellites have been recognized,among which(469219)Kamo’oalewa(provisionally designated as 2016 HO3)is currently considered the most stable and the closest of these.However,little is known about this particular asteroid or this class of near-Earth asteroids because of the difficulties of observing them.China has announced that Tianwen-2,the asteroid sample-return mission to Kamo’oalewa,will be launched in 2025.Here,we review the current knowledge of Kamo’oalewa in terms of its physical characteristics,dynamic evolution,surface environment,and origin,and we propose possible breakthroughs that the samples could bring concerning the asteroid Kamo’oalewa as an Earth quasi-satellite.Confirming the origin of Kamo’oalewa,from its prevailing provenance as debris of the Moon,could be a promising start to inferring the evolutionary history of the Moon.This history would probably include a more comprehensive view of the lunar farside and the origin of the asymmetry between the two sides of the Moon.Comparing the samples from the Moon and Kamo’oalewa would also provide new insights into the Earth wind.展开更多
In this paper,an image processing algorithm which is able to synthesize material textures of arbitrary shapes is proposed.The presented approach uses an arbitrary image to construct a structure layer of the material.T...In this paper,an image processing algorithm which is able to synthesize material textures of arbitrary shapes is proposed.The presented approach uses an arbitrary image to construct a structure layer of the material.The resulting structure layer is then used to constrain the material texture synthesis.The field of second-moment matrices is used to represent the structure layer.Many tests with various constraint images are conducted to ensure that the proposed approach accurately reproduces the visual aspects of the input material sample.The results demonstrate that the proposed algorithm is able to accurately synthesize arbitrary-shaped material textures while respecting the local characteristics of the exemplar.This paves the way toward the synthesis of 3D material textures of arbitrary shapes from 2D material samples,which has a wide application range in virtual material design and materials characterization.展开更多
Objective To evaluate the diagnostic value of histopathological examination of ultrasound-guided puncture biopsy samples in extrapulmonary tuberculosis(EPTB).Methods This study was conducted at the Shanghai Public Hea...Objective To evaluate the diagnostic value of histopathological examination of ultrasound-guided puncture biopsy samples in extrapulmonary tuberculosis(EPTB).Methods This study was conducted at the Shanghai Public Health Clinical Center.A total of 115patients underwent ultrasound-guided puncture biopsy,followed by MGIT 960 culture(culture),smear,Gene Xpert MTB/RIF(Xpert),and histopathological examination.These assays were performed to evaluate their effectiveness in diagnosing EPTB in comparison to two different diagnostic criteria:liquid culture and composite reference standard(CRS).Results When CRS was used as the reference standard,the sensitivity and specificity of culture,smear,Xpert,and histopathological examination were(44.83%,89.29%),(51.72%,89.29%),(70.11%,96.43%),and(85.06%,82.14%),respectively.Based on liquid culture tests,the sensitivity and specificity of smear,Xpert,and pathological examination were(66.67%,72.60%),(83.33%,63.01%),and(92.86%,45.21%),respectively.Histopathological examination showed the highest sensitivity but lowest specificity.Further,we found that the combination of Xpert and histopathological examination showed a sensitivity of 90.80%and a specificity of 89.29%.Conclusion Ultrasound-guided puncture sampling is safe and effective for the diagnosis of EPTB.Compared with culture,smear,and Xpert,histopathological examination showed higher sensitivity but lower specificity.The combination of histopathology with Xpert showed the best performance characteristics.展开更多
How to use a few defect samples to complete the defect classification is a key challenge in the production of mobile phone screens.An attention-relation network for the mobile phone screen defect classification is pro...How to use a few defect samples to complete the defect classification is a key challenge in the production of mobile phone screens.An attention-relation network for the mobile phone screen defect classification is proposed in this paper.The architecture of the attention-relation network contains two modules:a feature extract module and a feature metric module.Different from other few-shot models,an attention mechanism is applied to metric learning in our model to measure the distance between features,so as to pay attention to the correlation between features and suppress unwanted information.Besides,we combine dilated convolution and skip connection to extract more feature information for follow-up processing.We validate attention-relation network on the mobile phone screen defect dataset.The experimental results show that the classification accuracy of the attentionrelation network is 0.9486 under the 5-way 1-shot training strategy and 0.9039 under the 5-way 5-shot setting.It achieves the excellent effect of classification for mobile phone screen defects and outperforms with dominant advantages.展开更多
Perovskite solar cells(PsCs)have developed tremendously over the past decade.However,the key factors influencing the power conversion efficiency(PCE)of PSCs remain incompletely understood,due to the complexity and cou...Perovskite solar cells(PsCs)have developed tremendously over the past decade.However,the key factors influencing the power conversion efficiency(PCE)of PSCs remain incompletely understood,due to the complexity and coupling of these structural and compositional parameters.In this research,we demon-strate an effective approach to optimize PSCs performance via machine learning(ML).To address chal-lenges posed by limited samples,we propose a feature mask(FM)method,which augments training samples through feature transformation rather than synthetic data.Using this approach,squeeze-and-excitation residual network(SEResNet)model achieves an accuracy with a root-mean-square-error(RMSE)of 0.833%and a Pearson's correlation coefficient(r)of 0.980.Furthermore,we employ the permu-tation importance(PI)algorithm to investigate key features for PCE.Subsequently,we predict PCE through high-throughput screenings,in which we study the relationship between PCE and chemical com-positions.After that,we conduct experiments to validate the consistency between predicted results by ML and experimental results.In this work,ML demonstrates the capability to predict device performance,extract key parameters from complex systems,and accelerate the transition from laboratory findings to commercialapplications.展开更多
Accurate and reliable fault detection is essential for the safe operation of electric vehicles.Support vector data description(SVDD)has been widely used in the field of fault detection.However,constructing the hypersp...Accurate and reliable fault detection is essential for the safe operation of electric vehicles.Support vector data description(SVDD)has been widely used in the field of fault detection.However,constructing the hypersphere boundary only describes the distribution of unlabeled samples,while the distribution of faulty samples cannot be effectively described and easilymisses detecting faulty data due to the imbalance of sample distribution.Meanwhile,selecting parameters is critical to the detection performance,and empirical parameterization is generally timeconsuming and laborious and may not result in finding the optimal parameters.Therefore,this paper proposes a semi-supervised data-driven method based on which the SVDD algorithm is improved and achieves excellent fault detection performance.By incorporating faulty samples into the underlying SVDD model,training deals better with the problem of missing detection of faulty samples caused by the imbalance in the distribution of abnormal samples,and the hypersphere boundary ismodified to classify the samplesmore accurately.The Bayesian Optimization NSVDD(BO-NSVDD)model was constructed to quickly and accurately optimize hyperparameter combinations.In the experiments,electric vehicle operation data with four common fault types are used to evaluate the performance with other five models,and the results show that the BO-NSVDD model presents superior detection performance for each type of fault data,especially in the imperceptible early and minor faults,which has seen very obvious advantages.Finally,the strong robustness of the proposed method is verified by adding different intensities of noise in the dataset.展开更多
The encapsulation of lunar samples is a core research area in the third phase of the Chinese Lunar Exploration Program.The seal assembly,opening and closing mechanism(OCM),and locking mechanism are the core components...The encapsulation of lunar samples is a core research area in the third phase of the Chinese Lunar Exploration Program.The seal assembly,opening and closing mechanism(OCM),and locking mechanism are the core components of the encapsulation device of the lunar samples,and the requirements of a tight seal,lightweight,and low power make the design of these core components difficult.In this study,a combined sealing assembly,OCM,and locking mechanism were investigated for the device.The sealing architecture consists of rubber and an Ag-In alloy,and a theory was built to analyze the seal.Experiments of the electroplate Au coating on the knife-edge revealed that the hermetic seal can be significantly improved.The driving principle for coaxial double-helical pairs was investigated and used to design the OCM.Moreover,a locking mechanism was created using an electric initiating explosive device with orifice damping.By optimizing the design,the output parameters were adjusted to meet the requirements of the lunar explorer.The experimental results showed that the helium leak rate of the test pieces were not more than 5×10^(-11) Pa·m^(3)·s^(-1),the minimum power of the OCM was 0.3 W,and the total weight of the principle prototype was 2.9 kg.The explosive driven locking mechanism has low impact.This investigation solved the difficulties in achieving tight seal,light weight,and low power for the lunar explorer,and the results can also be used to explore other extraterrestrial objects in the future.展开更多
The deep mining of coal resources is accompanied by severe environmental challenges and various potential engineering hazards.The implementation of NPR(negative Poisson's ratio)bolts are capable of controlling lar...The deep mining of coal resources is accompanied by severe environmental challenges and various potential engineering hazards.The implementation of NPR(negative Poisson's ratio)bolts are capable of controlling large deformations in the surrounding rock effectively.This paper focuses on studying the mechanical properties of the NPR bolt under static disturbance load.The deep nonlinear mechanical experimental system was used to study the mechanical behavior of rock samples with different anchored types(unanchored/PR anchored/2G NPR anchored)under static disturbance load.The whole process of rock samples was taken by high-speed camera to obtain the real-time failure characteristics under static disturbance load.At the same time,the acoustic emission signal was collected to obtain the key characteristic parameters of acoustic emission such as acoustic emission count,energy,and frequency.The deformation at the failure of the samples was calculated and analyzed by digital speckle software.The findings indicate that the failure mode of rock is influenced by different types of anchoring.The peak failure strength of 2G NPR bolt anchored rock samples exhibits an increase of 6.5%when compared to the unanchored rock samples.The cumulative count and cumulative energy of acoustic emission exhibit a decrease of 62.16%and 62.90%,respectively.The maximum deformation of bearing capacity exhibits an increase of 59.27%,while the failure time demonstrates a delay of 42.86%.The peak failure strength of the 2G NPR bolt anchored ones under static disturbance load exhibits an increase of 5.94%when compared to the rock anchored by PR(Poisson's ratio)bolt.The cumulative count and cumulative energy of acoustic emission exhibit a decrease of 47.16%and 43.86%,respectively.The maximum deformation of the bearing capacity exhibits an increase of 50.43%,and the failure time demonstrates a delay of 32%.After anchoring by 2G NPR bolt,anchoring support effectively reduces the risk of damage caused by static disturbance load.These results demonstrate that the support effect of 2G NPR bolt materials surpasses that of PR bolt.展开更多
In order to solve the problems of weak prediction stability and generalization ability of a neural network algorithm model in the yarn quality prediction research for small samples,a prediction model based on an AdaBo...In order to solve the problems of weak prediction stability and generalization ability of a neural network algorithm model in the yarn quality prediction research for small samples,a prediction model based on an AdaBoost algorithm(AdaBoost model) was established.A prediction model based on a linear regression algorithm(LR model) and a prediction model based on a multi-layer perceptron neural network algorithm(MLP model) were established for comparison.The prediction experiments of the yarn evenness and the yarn strength were implemented.Determination coefficients and prediction errors were used to evaluate the prediction accuracy of these models,and the K-fold cross validation was used to evaluate the generalization ability of these models.In the prediction experiments,the determination coefficient of the yarn evenness prediction result of the AdaBoost model is 76% and 87% higher than that of the LR model and the MLP model,respectively.The determination coefficient of the yarn strength prediction result of the AdaBoost model is slightly higher than that of the other two models.Considering that the yarn evenness dataset has a weaker linear relationship with the cotton dataset than that of the yarn strength dataset in this paper,the AdaBoost model has the best adaptability for the nonlinear dataset among the three models.In addition,the AdaBoost model shows generally better results in the cross-validation experiments and the series of prediction experiments at eight different training set sample sizes.It is proved that the AdaBoost model not only has good prediction accuracy but also has good prediction stability and generalization ability for small samples.展开更多
Recently,one of the main challenges facing the smart grid is insufficient computing resources and intermittent energy supply for various distributed components(such as monitoring systems for renewable energy power sta...Recently,one of the main challenges facing the smart grid is insufficient computing resources and intermittent energy supply for various distributed components(such as monitoring systems for renewable energy power stations).To solve the problem,we propose an energy harvesting based task scheduling and resource management framework to provide robust and low-cost edge computing services for smart grid.First,we formulate an energy consumption minimization problem with regard to task offloading,time switching,and resource allocation for mobile devices,which can be decoupled and transformed into a typical knapsack problem.Then,solutions are derived by two different algorithms.Furthermore,we deploy renewable energy and energy storage units at edge servers to tackle intermittency and instability problems.Finally,we design an energy management algorithm based on sampling average approximation for edge computing servers to derive the optimal charging/discharging strategies,number of energy storage units,and renewable energy utilization.The simulation results show the efficiency and superiority of our proposed framework.展开更多
In this study,eight different varieties of maize seeds were used as the research objects.Conduct 81 types of combined preprocessing on the original spectra.Through comparison,Savitzky-Golay(SG)-multivariate scattering...In this study,eight different varieties of maize seeds were used as the research objects.Conduct 81 types of combined preprocessing on the original spectra.Through comparison,Savitzky-Golay(SG)-multivariate scattering correction(MSC)-maximum-minimum normalization(MN)was identified as the optimal preprocessing technique.The competitive adaptive reweighted sampling(CARS),successive projections algorithm(SPA),and their combined methods were employed to extract feature wavelengths.Classification models based on back propagation(BP),support vector machine(SVM),random forest(RF),and partial least squares(PLS)were established using full-band data and feature wavelengths.Among all models,the(CARS-SPA)-BP model achieved the highest accuracy rate of 98.44%.This study offers novel insights and methodologies for the rapid and accurate identification of corn seeds as well as other crop seeds.展开更多
One of the detection objectives of the Chinese Asteroid Exploration mission is to investigate the space environment near the Main-belt Comet(MBC,Active Asteroid)311P/PANSTARRS.This paper outlines the scientific object...One of the detection objectives of the Chinese Asteroid Exploration mission is to investigate the space environment near the Main-belt Comet(MBC,Active Asteroid)311P/PANSTARRS.This paper outlines the scientific objectives,measurement targets,and measurement requirements for the proposed Gas and Ion Analyzer(GIA).The GIA is designed for in-situ mass spectrometry of neutral gases and low-energy ions,such as hydrogen,carbon,and oxygen,in the vicinity of 311P.Ion sampling techniques are essential for the GIA's Time-of-Flight(TOF)mass analysis capabilities.In this paper,we present an enhanced ion sampling technique through the development of an ion attraction model and an ion source model.The ion attraction model demonstrates that adjusting attraction grid voltage can enhance the detection efficiency of low-energy ions and mitigate the repulsive force of ions during sampling,which is influenced by the satellite's surface positive charging.The ion source model simulates the processes of gas ionization and ion multiplication.Simulation results indicate that the GIA can achieve a lower pressure limit below 10-13Pa and possess a dynamic range exceeding 10~9.These performances ensure the generation of ions with stable and consistent current,which is crucial for high-resolution and broad dynamic range mass spectrometer analysis.Preliminary testing experiments have verified GIA's capability to detect gas compositions such as H2O and N2.In-situ measurements near 311P using GIA are expected to significantly contribute to our understanding of asteroid activity mechanisms,the evolution of the atmospheric and ionized environments of main-belt comets,the interactions with solar wind,and the origin of Earth's water.展开更多
Electro-Optic Sampling(EOS)detection technique has been widely used in terahertz science and tech⁃nology,and it also can measure the field time waveform of the few-cycle laser pulse.Its frequency response and band lim...Electro-Optic Sampling(EOS)detection technique has been widely used in terahertz science and tech⁃nology,and it also can measure the field time waveform of the few-cycle laser pulse.Its frequency response and band limitation are determined directly by the electro-optic crystal and duration of the probe laser pulse.Here,we investigate the performance of the EOS with thin GaSe crystal in the measurement of the mid-infrared few-cycle la⁃ser pulse.The shift of the central frequency and change of the bandwidth induced by the EOS detection are calcu⁃lated,and then the pulse distortions induced in this detection process are discussed.It is found that this technique produces a red-shift of the central frequency and narrowing of the bandwidth.These changings decrease when the laser wavelength increases from 2μm to 10μm.This work can help to estimate the performance of the EOS de⁃tection technique in the mid-infrared band and offer a reference for the related experiment as well.展开更多
[Objective] This study aimed to compare the residue situation of cimaterol,a kind of forbidden veterinary drug in hair, urine and flesh of pig, so as to provide theoretical basis for monitoring veterinary drug residue...[Objective] This study aimed to compare the residue situation of cimaterol,a kind of forbidden veterinary drug in hair, urine and flesh of pig, so as to provide theoretical basis for monitoring veterinary drug residue in bred animals. [Method]Total three different concentrations of cimaterol were administered to pigs, and the residue amounts of cimaterol in pig hair, urine and flesh were monitored at different raising stage. [Result] During the administration period, the residue amount of cimaterol was highest in urine, so urine is the suitable sample for rapid detection of cimaterol in manufacturing enterprises. Cimaterol could be accumulated in pig hair,where cimaterol was metabolized slowly. Thus, pig hair can be used as the test sample for tracing illegal use of veterinary drugs and for vivo detection. Flesh can be used as test sample for direct judgment whether cimaterol residue exceeds the relevant standard. [Conclusion] This study will provide certain theoretical basis for drug monitor in animal husbandry.展开更多
A modified separation method has been developed for determinating polychlorinated biphenyl congeners in environmental samples. Direct treatment of extract with concentrated HzSO4 was employed in the first step for rem...A modified separation method has been developed for determinating polychlorinated biphenyl congeners in environmental samples. Direct treatment of extract with concentrated HzSO4 was employed in the first step for removal of lipids and other interfering substances, then a joint column of alumina-silica gel(Ag+) was applied to separate PCBs fraction from HCH, DDT and its analogs. After this separation, the PCBs fraction was analyzed by capillary gas chromatography with ECD detector and confirmed by GC/MS. The recoveries of individual congeners in Aroclor 1254 through the separation are about 79%-84%. The method is very efficient and useful for determination of trace amount of PCB congeners in environmental samples.展开更多
基金the Key National Natural Science Foundation of China(No.U1864211)the National Natural Science Foundation of China(No.11772191)the Natural Science Foundation of Shanghai(No.21ZR1431500)。
文摘Industrial data mining usually deals with data from different sources.These heterogeneous datasets describe the same object in different views.However,samples from some of the datasets may be lost.Then the remaining samples do not correspond one-to-one correctly.Mismatched datasets caused by missing samples make the industrial data unavailable for further machine learning.In order to align the mismatched samples,this article presents a cooperative iteration matching method(CIMM)based on the modified dynamic time warping(DTW).The proposed method regards the sequentially accumulated industrial data as the time series.Mismatched samples are aligned by the DTW.In addition,dynamic constraints are applied to the warping distance of the DTW process to make the alignment more efficient.Then a series of models are trained with the cumulated samples iteratively.Several groups of numerical experiments on different missing patterns and missing locations are designed and analyzed to prove the effectiveness and the applicability of the proposed method.
文摘Geological samples often contain significant amounts of iron,which,although not typically the target element,can substantially interfere with the analysis of other elements of interest.To mitigate these interferences,amidoximebased radiation grafted adsorbents have been identified as effective for iron removal.In this study,an amidoximefunctionalized,radiation-grafted adsorbent synthesized from polypropylene waste(PPw-g-AO-10)was employed to remove iron from leached geological samples.The adsorption process was systematically optimized by investigating the effects of pH,contact time,adsorbent dosage,and initial ferric ion concentration.Under optimal conditions-pH1.4,a contact time of 90 min,and an initial ferric ion concentration of 4500 mg/L-the adsorbent exhibited a maximum iron adsorption capacity of 269.02 mg/g.After optimizing the critical adsorption parameters,the adsorbent was applied to the leached geological samples,achieving a 91%removal of the iron content.The adsorbent was regenerated through two consecutive cycles using 0.2 N HNO_(3),achieving a regeneration efficiency of 65%.These findings confirm the efficacy of the synthesized PPw-g-AO-10 as a cost-effective and eco-friendly adsorbent for successfully removing iron from leached geological matrices while maintaining a reasonable degree of reusability.
基金supported by grants from the National Natural Science Foundation of China(grant numbers:82370195,82270203,81770211)the Fundamental Research Funds for the Central Univer-sities(grant number:2022CDJYGRH-001)Chongqing Technology Innovation and Application Development Special Key Project(grant number:CSTB2024TIAD-KPX0031).
文摘Flow cytometry(FCM),characterized by its simplicity,rapid processing,multiparameter analysis,and high sen-sitivity,is widely used in the diagnosis,treatment,and prognosis of hematological malignancies.FCM testing of tissue samples not only aids in diagnosing and classifying hematological cancers,but also enables the detection of solid tumors.Its ability to detect numerous marker parameters from small samples is particularly useful when dealing with limited cell quantities,such as in fine-needle biopsy samples.This attribute not only addresses the challenge posed by small sample sizes,but also boosts the sensitivity of tumor cell detection.The significance of FCM in clinical and pathological applications continues to grow.To standardize the use of FCM in detecting hematological malignant cells in tissue samples and to improve quality control during the detection process,experts from the Cell Analysis Professional Committee of the Chinese Society of Biotechnology jointly drafted and agreed upon this consensus.This consensus was formulated based on current literature and clinical practices of all experts across clinical,laboratory,and pathological fields in China.It outlines a comprehensive workflow of FCM-based assay for the detection of hematological malignancies in tissue samples,including report content,interpretation,quality control,and key considerations.Additionally,it provides recommendations on antibody panel designs and analytical approaches to enhancing FCM tests,particularly in cases with limited sample sizes.
基金supported by grants from the Human Resources Development program(Grant No.20204010600250)the Training Program of CCUS for the Green Growth(Grant No.20214000000500)by the Korea Institute of Energy Technology Evaluation and Planning(KETEP)funded by the Ministry of Trade,Industry,and Energy of the Korean Government(MOTIE).
文摘Three-dimensional printing(3DP)offers valuable insight into the characterization of natural rocks and the verification of theoretical models due to its high reproducibility and accurate replication of complex defects such as cracks and pores.In this study,3DP gypsum samples with different printing directions were subjected to a series of uniaxial compression tests with in situ micro-computed tomography(micro-CT)scanning to quantitatively investigate their mechanical anisotropic properties and damage evolution characteristics.Based on the two-dimensional(2D)CT images obtained at different scanning steps,a novel void ratio variable was derived using the mean value and variance of CT intensity.Additionally,a constitutive model was formulated incorporating the proposed damage variable,utilizing the void ratio variable.The crack evolution and crack morphology of 3DP gypsum samples were obtained and analyzed using the 3D models reconstructed from the CT images.The results indicate that 3DP gypsum samples exhibit mechanical anisotropic characteristics similar to those found in naturally sedimentary rocks.The mechanical anisotropy is attributed to the bedding planes formed between adjacent layers and pillar-like structures along the printing direction formed by CaSO_(4)·2H_(2)O crystals of needle-like morphology.The mean gray intensity of the voids has a positive linear relationship with the threshold value,while the CT variance and void ratio have concave and convex relationships,respectively.The constitutive model can effectively match the stress–strain curves obtained from uniaxial compression experiments.This study provides comprehensive explanations of the failure modes and anisotropic mechanisms of 3DP gypsum samples,which is important for characterizing and understanding the failure mechanism and microstructural evolution of 3DP rocks when modeling natural rock behavior.
基金supported by the Innovation Driven Development Foundation of Guangxi(No.AD22080035)the Open Project Funding of the Key Laboratory of Tropical Marine Ecosystem and Bioresource,Ministry of Natural Resources(No.2023-QN04)+1 种基金the Guangdong Provincial Ordinary University Youth Innovative Talent Project in 2024(No.2024KQNCX134)the Guangdong Provincial Special Fund Project for Talent Development Strategy in 2024(No.2024R3005).
文摘The investigation of whether sediment samples contain representative grain size distribution information is important for the accurate extraction of sediment characteristics and conduct of related sedimentary record studies.This study comparatively analyzed the numerical and qualitative differences and the degree of correlation of 36 sets of the characteristic parameters of surface sediment parallel sample grain size distribution from three sampling profiles at Jinsha Bay Beach in Zhanjiang,western Guangdong.At each sampling point,five parallel subsamples were established at intervals of 0,10,20,50,and 100 cm along the coastline.The research findings indicate the following:1)relatively large differences in the mean values of the different parallel samples(0.19–0.34Φ),with smaller differences observed in other characteristic grain sizes(D_(10),D_(50),and D_(90));2)small differences in characteristic values among various parallel sample grain size parameters,with at least 33%of the combinations of qualitative results showing inconsistency;3)50%of the regression equations between the skewness of different parallel samples displaying no significant correlation;4)relative deviations of−47.91%to 27.63%and−49.20%to 2.08%existing between the particle size parameters of a single sample and parallel samples(with the average obtained)at intervals of 10 and 50 cm,respectively.As such,small spatial differences,even within 100 cm,can considerably affect grain size parameters.Given the uncertain reasons underlying the representativeness of the samples,which may only cover the area immediately surrounding the sampling station,researchers are advised to design parallel sample collection strategies based on the spatiotemporal distribution characteristics of the parameters of interest during sediment sample collection.This study provides a typical case of the comparative analysis of parallel sample grain size parameters,with a focus on small spatial beach sediment,which contributes to the enhanced understanding of the accuracy and reliability of sediment sample collection strategies and extraction of grain size information.
基金supported by the National Natural Science Foundation of China(Grant Nos.42241106 and 42388101).
文摘The exploration of asteroids has received increasing attention since the 1990s because of the unique information these objects contain about the history of the early solar system.Quasi-satellites are a population of asteroids that co-orbit closely with,but are outside the gravitational control of,the planet.So far,only five Earth quasi-satellites have been recognized,among which(469219)Kamo’oalewa(provisionally designated as 2016 HO3)is currently considered the most stable and the closest of these.However,little is known about this particular asteroid or this class of near-Earth asteroids because of the difficulties of observing them.China has announced that Tianwen-2,the asteroid sample-return mission to Kamo’oalewa,will be launched in 2025.Here,we review the current knowledge of Kamo’oalewa in terms of its physical characteristics,dynamic evolution,surface environment,and origin,and we propose possible breakthroughs that the samples could bring concerning the asteroid Kamo’oalewa as an Earth quasi-satellite.Confirming the origin of Kamo’oalewa,from its prevailing provenance as debris of the Moon,could be a promising start to inferring the evolutionary history of the Moon.This history would probably include a more comprehensive view of the lunar farside and the origin of the asymmetry between the two sides of the Moon.Comparing the samples from the Moon and Kamo’oalewa would also provide new insights into the Earth wind.
文摘In this paper,an image processing algorithm which is able to synthesize material textures of arbitrary shapes is proposed.The presented approach uses an arbitrary image to construct a structure layer of the material.The resulting structure layer is then used to constrain the material texture synthesis.The field of second-moment matrices is used to represent the structure layer.Many tests with various constraint images are conducted to ensure that the proposed approach accurately reproduces the visual aspects of the input material sample.The results demonstrate that the proposed algorithm is able to accurately synthesize arbitrary-shaped material textures while respecting the local characteristics of the exemplar.This paves the way toward the synthesis of 3D material textures of arbitrary shapes from 2D material samples,which has a wide application range in virtual material design and materials characterization.
基金funded by the grants from the National Key Research and Development Program of China[2021YFC2301503,2022YFC2302900]the National Natural and Science Foundation of China[82171739,82171815,81873884]。
文摘Objective To evaluate the diagnostic value of histopathological examination of ultrasound-guided puncture biopsy samples in extrapulmonary tuberculosis(EPTB).Methods This study was conducted at the Shanghai Public Health Clinical Center.A total of 115patients underwent ultrasound-guided puncture biopsy,followed by MGIT 960 culture(culture),smear,Gene Xpert MTB/RIF(Xpert),and histopathological examination.These assays were performed to evaluate their effectiveness in diagnosing EPTB in comparison to two different diagnostic criteria:liquid culture and composite reference standard(CRS).Results When CRS was used as the reference standard,the sensitivity and specificity of culture,smear,Xpert,and histopathological examination were(44.83%,89.29%),(51.72%,89.29%),(70.11%,96.43%),and(85.06%,82.14%),respectively.Based on liquid culture tests,the sensitivity and specificity of smear,Xpert,and pathological examination were(66.67%,72.60%),(83.33%,63.01%),and(92.86%,45.21%),respectively.Histopathological examination showed the highest sensitivity but lowest specificity.Further,we found that the combination of Xpert and histopathological examination showed a sensitivity of 90.80%and a specificity of 89.29%.Conclusion Ultrasound-guided puncture sampling is safe and effective for the diagnosis of EPTB.Compared with culture,smear,and Xpert,histopathological examination showed higher sensitivity but lower specificity.The combination of histopathology with Xpert showed the best performance characteristics.
文摘How to use a few defect samples to complete the defect classification is a key challenge in the production of mobile phone screens.An attention-relation network for the mobile phone screen defect classification is proposed in this paper.The architecture of the attention-relation network contains two modules:a feature extract module and a feature metric module.Different from other few-shot models,an attention mechanism is applied to metric learning in our model to measure the distance between features,so as to pay attention to the correlation between features and suppress unwanted information.Besides,we combine dilated convolution and skip connection to extract more feature information for follow-up processing.We validate attention-relation network on the mobile phone screen defect dataset.The experimental results show that the classification accuracy of the attentionrelation network is 0.9486 under the 5-way 1-shot training strategy and 0.9039 under the 5-way 5-shot setting.It achieves the excellent effect of classification for mobile phone screen defects and outperforms with dominant advantages.
基金supported by the National Key Research and Development Program (2022YFF0609504)the National Natural Science Foundation of China (61974126,51902273,62005230,62001405)the Natural Science Foundation of Fujian Province of China (No.2021J06009)
文摘Perovskite solar cells(PsCs)have developed tremendously over the past decade.However,the key factors influencing the power conversion efficiency(PCE)of PSCs remain incompletely understood,due to the complexity and coupling of these structural and compositional parameters.In this research,we demon-strate an effective approach to optimize PSCs performance via machine learning(ML).To address chal-lenges posed by limited samples,we propose a feature mask(FM)method,which augments training samples through feature transformation rather than synthetic data.Using this approach,squeeze-and-excitation residual network(SEResNet)model achieves an accuracy with a root-mean-square-error(RMSE)of 0.833%and a Pearson's correlation coefficient(r)of 0.980.Furthermore,we employ the permu-tation importance(PI)algorithm to investigate key features for PCE.Subsequently,we predict PCE through high-throughput screenings,in which we study the relationship between PCE and chemical com-positions.After that,we conduct experiments to validate the consistency between predicted results by ML and experimental results.In this work,ML demonstrates the capability to predict device performance,extract key parameters from complex systems,and accelerate the transition from laboratory findings to commercialapplications.
基金supported partially by NationalNatural Science Foundation of China(NSFC)(No.U21A20146)Collaborative Innovation Project of Anhui Universities(No.GXXT-2020-070)+8 种基金Cooperation Project of Anhui Future Technology Research Institute and Enterprise(No.2023qyhz32)Development of a New Dynamic Life Prediction Technology for Energy Storage Batteries(No.KH10003598)Opening Project of Key Laboratory of Electric Drive and Control of Anhui Province(No.DQKJ202304)Anhui Provincial Department of Education New Era Education Quality Project(No.2023dshwyx019)Special Fund for Collaborative Innovation between Anhui Polytechnic University and Jiujiang District(No.2022cyxtb10)Key Research and Development Program of Wuhu City(No.2022yf42)Open Research Fund of Anhui Key Laboratory of Detection Technology and Energy Saving Devices(No.JCKJ2021B06)Anhui Provincial Graduate Student Innovation and Entrepreneurship Practice Project(No.2022cxcysj123)Key Scientific Research Project for Anhui Universities(No.2022AH050981).
文摘Accurate and reliable fault detection is essential for the safe operation of electric vehicles.Support vector data description(SVDD)has been widely used in the field of fault detection.However,constructing the hypersphere boundary only describes the distribution of unlabeled samples,while the distribution of faulty samples cannot be effectively described and easilymisses detecting faulty data due to the imbalance of sample distribution.Meanwhile,selecting parameters is critical to the detection performance,and empirical parameterization is generally timeconsuming and laborious and may not result in finding the optimal parameters.Therefore,this paper proposes a semi-supervised data-driven method based on which the SVDD algorithm is improved and achieves excellent fault detection performance.By incorporating faulty samples into the underlying SVDD model,training deals better with the problem of missing detection of faulty samples caused by the imbalance in the distribution of abnormal samples,and the hypersphere boundary ismodified to classify the samplesmore accurately.The Bayesian Optimization NSVDD(BO-NSVDD)model was constructed to quickly and accurately optimize hyperparameter combinations.In the experiments,electric vehicle operation data with four common fault types are used to evaluate the performance with other five models,and the results show that the BO-NSVDD model presents superior detection performance for each type of fault data,especially in the imperceptible early and minor faults,which has seen very obvious advantages.Finally,the strong robustness of the proposed method is verified by adding different intensities of noise in the dataset.
基金Supported by Research Foundation of CLEP of China (Grant No.TY3Q20110003)。
文摘The encapsulation of lunar samples is a core research area in the third phase of the Chinese Lunar Exploration Program.The seal assembly,opening and closing mechanism(OCM),and locking mechanism are the core components of the encapsulation device of the lunar samples,and the requirements of a tight seal,lightweight,and low power make the design of these core components difficult.In this study,a combined sealing assembly,OCM,and locking mechanism were investigated for the device.The sealing architecture consists of rubber and an Ag-In alloy,and a theory was built to analyze the seal.Experiments of the electroplate Au coating on the knife-edge revealed that the hermetic seal can be significantly improved.The driving principle for coaxial double-helical pairs was investigated and used to design the OCM.Moreover,a locking mechanism was created using an electric initiating explosive device with orifice damping.By optimizing the design,the output parameters were adjusted to meet the requirements of the lunar explorer.The experimental results showed that the helium leak rate of the test pieces were not more than 5×10^(-11) Pa·m^(3)·s^(-1),the minimum power of the OCM was 0.3 W,and the total weight of the principle prototype was 2.9 kg.The explosive driven locking mechanism has low impact.This investigation solved the difficulties in achieving tight seal,light weight,and low power for the lunar explorer,and the results can also be used to explore other extraterrestrial objects in the future.
基金provided by the National Natural Science Foundation of China(52074300)the Program of China Scholarship Council(202206430024)+2 种基金the National Natural Science Foundation of China Youth Science(52104139)Yueqi Young Scholars Project of China University of Mining and Technology Beijing(2602021RC84)Guizhou province science and technology planning project([2020]3007,[2020]3008)。
文摘The deep mining of coal resources is accompanied by severe environmental challenges and various potential engineering hazards.The implementation of NPR(negative Poisson's ratio)bolts are capable of controlling large deformations in the surrounding rock effectively.This paper focuses on studying the mechanical properties of the NPR bolt under static disturbance load.The deep nonlinear mechanical experimental system was used to study the mechanical behavior of rock samples with different anchored types(unanchored/PR anchored/2G NPR anchored)under static disturbance load.The whole process of rock samples was taken by high-speed camera to obtain the real-time failure characteristics under static disturbance load.At the same time,the acoustic emission signal was collected to obtain the key characteristic parameters of acoustic emission such as acoustic emission count,energy,and frequency.The deformation at the failure of the samples was calculated and analyzed by digital speckle software.The findings indicate that the failure mode of rock is influenced by different types of anchoring.The peak failure strength of 2G NPR bolt anchored rock samples exhibits an increase of 6.5%when compared to the unanchored rock samples.The cumulative count and cumulative energy of acoustic emission exhibit a decrease of 62.16%and 62.90%,respectively.The maximum deformation of bearing capacity exhibits an increase of 59.27%,while the failure time demonstrates a delay of 42.86%.The peak failure strength of the 2G NPR bolt anchored ones under static disturbance load exhibits an increase of 5.94%when compared to the rock anchored by PR(Poisson's ratio)bolt.The cumulative count and cumulative energy of acoustic emission exhibit a decrease of 47.16%and 43.86%,respectively.The maximum deformation of the bearing capacity exhibits an increase of 50.43%,and the failure time demonstrates a delay of 32%.After anchoring by 2G NPR bolt,anchoring support effectively reduces the risk of damage caused by static disturbance load.These results demonstrate that the support effect of 2G NPR bolt materials surpasses that of PR bolt.
文摘In order to solve the problems of weak prediction stability and generalization ability of a neural network algorithm model in the yarn quality prediction research for small samples,a prediction model based on an AdaBoost algorithm(AdaBoost model) was established.A prediction model based on a linear regression algorithm(LR model) and a prediction model based on a multi-layer perceptron neural network algorithm(MLP model) were established for comparison.The prediction experiments of the yarn evenness and the yarn strength were implemented.Determination coefficients and prediction errors were used to evaluate the prediction accuracy of these models,and the K-fold cross validation was used to evaluate the generalization ability of these models.In the prediction experiments,the determination coefficient of the yarn evenness prediction result of the AdaBoost model is 76% and 87% higher than that of the LR model and the MLP model,respectively.The determination coefficient of the yarn strength prediction result of the AdaBoost model is slightly higher than that of the other two models.Considering that the yarn evenness dataset has a weaker linear relationship with the cotton dataset than that of the yarn strength dataset in this paper,the AdaBoost model has the best adaptability for the nonlinear dataset among the three models.In addition,the AdaBoost model shows generally better results in the cross-validation experiments and the series of prediction experiments at eight different training set sample sizes.It is proved that the AdaBoost model not only has good prediction accuracy but also has good prediction stability and generalization ability for small samples.
基金supported in part by the National Natural Science Foundation of China under Grant No.61473066in part by the Natural Science Foundation of Hebei Province under Grant No.F2021501020+2 种基金in part by the S&T Program of Qinhuangdao under Grant No.202401A195in part by the Science Research Project of Hebei Education Department under Grant No.QN2025008in part by the Innovation Capability Improvement Plan Project of Hebei Province under Grant No.22567637H
文摘Recently,one of the main challenges facing the smart grid is insufficient computing resources and intermittent energy supply for various distributed components(such as monitoring systems for renewable energy power stations).To solve the problem,we propose an energy harvesting based task scheduling and resource management framework to provide robust and low-cost edge computing services for smart grid.First,we formulate an energy consumption minimization problem with regard to task offloading,time switching,and resource allocation for mobile devices,which can be decoupled and transformed into a typical knapsack problem.Then,solutions are derived by two different algorithms.Furthermore,we deploy renewable energy and energy storage units at edge servers to tackle intermittency and instability problems.Finally,we design an energy management algorithm based on sampling average approximation for edge computing servers to derive the optimal charging/discharging strategies,number of energy storage units,and renewable energy utilization.The simulation results show the efficiency and superiority of our proposed framework.
基金supported by the Science and Technology Development Plan Project of Jilin Provincial Department of Science and Technology (No.20220203112S)the Jilin Provincial Department of Education Science and Technology Research Project (No.JJKH20210039KJ)。
文摘In this study,eight different varieties of maize seeds were used as the research objects.Conduct 81 types of combined preprocessing on the original spectra.Through comparison,Savitzky-Golay(SG)-multivariate scattering correction(MSC)-maximum-minimum normalization(MN)was identified as the optimal preprocessing technique.The competitive adaptive reweighted sampling(CARS),successive projections algorithm(SPA),and their combined methods were employed to extract feature wavelengths.Classification models based on back propagation(BP),support vector machine(SVM),random forest(RF),and partial least squares(PLS)were established using full-band data and feature wavelengths.Among all models,the(CARS-SPA)-BP model achieved the highest accuracy rate of 98.44%.This study offers novel insights and methodologies for the rapid and accurate identification of corn seeds as well as other crop seeds.
基金Supported by the National Natural Science Foundation of China(42474239,41204128)China National Space Administration(Pre-research project on Civil Aerospace Technologies No.D010301)Strategic Priority Research Program of the Chinese Academy of Sciences(XDA17010303)。
文摘One of the detection objectives of the Chinese Asteroid Exploration mission is to investigate the space environment near the Main-belt Comet(MBC,Active Asteroid)311P/PANSTARRS.This paper outlines the scientific objectives,measurement targets,and measurement requirements for the proposed Gas and Ion Analyzer(GIA).The GIA is designed for in-situ mass spectrometry of neutral gases and low-energy ions,such as hydrogen,carbon,and oxygen,in the vicinity of 311P.Ion sampling techniques are essential for the GIA's Time-of-Flight(TOF)mass analysis capabilities.In this paper,we present an enhanced ion sampling technique through the development of an ion attraction model and an ion source model.The ion attraction model demonstrates that adjusting attraction grid voltage can enhance the detection efficiency of low-energy ions and mitigate the repulsive force of ions during sampling,which is influenced by the satellite's surface positive charging.The ion source model simulates the processes of gas ionization and ion multiplication.Simulation results indicate that the GIA can achieve a lower pressure limit below 10-13Pa and possess a dynamic range exceeding 10~9.These performances ensure the generation of ions with stable and consistent current,which is crucial for high-resolution and broad dynamic range mass spectrometer analysis.Preliminary testing experiments have verified GIA's capability to detect gas compositions such as H2O and N2.In-situ measurements near 311P using GIA are expected to significantly contribute to our understanding of asteroid activity mechanisms,the evolution of the atmospheric and ionized environments of main-belt comets,the interactions with solar wind,and the origin of Earth's water.
基金Supported by the National Natural Science Foundation of China(12064028)Jiangxi Provincial Natural Science Foundation(20232BAB201045).
文摘Electro-Optic Sampling(EOS)detection technique has been widely used in terahertz science and tech⁃nology,and it also can measure the field time waveform of the few-cycle laser pulse.Its frequency response and band limitation are determined directly by the electro-optic crystal and duration of the probe laser pulse.Here,we investigate the performance of the EOS with thin GaSe crystal in the measurement of the mid-infrared few-cycle la⁃ser pulse.The shift of the central frequency and change of the bandwidth induced by the EOS detection are calcu⁃lated,and then the pulse distortions induced in this detection process are discussed.It is found that this technique produces a red-shift of the central frequency and narrowing of the bandwidth.These changings decrease when the laser wavelength increases from 2μm to 10μm.This work can help to estimate the performance of the EOS de⁃tection technique in the mid-infrared band and offer a reference for the related experiment as well.
基金Supported by Key Science and Technology Program(GKZ1222003-2-2)~~
文摘[Objective] This study aimed to compare the residue situation of cimaterol,a kind of forbidden veterinary drug in hair, urine and flesh of pig, so as to provide theoretical basis for monitoring veterinary drug residue in bred animals. [Method]Total three different concentrations of cimaterol were administered to pigs, and the residue amounts of cimaterol in pig hair, urine and flesh were monitored at different raising stage. [Result] During the administration period, the residue amount of cimaterol was highest in urine, so urine is the suitable sample for rapid detection of cimaterol in manufacturing enterprises. Cimaterol could be accumulated in pig hair,where cimaterol was metabolized slowly. Thus, pig hair can be used as the test sample for tracing illegal use of veterinary drugs and for vivo detection. Flesh can be used as test sample for direct judgment whether cimaterol residue exceeds the relevant standard. [Conclusion] This study will provide certain theoretical basis for drug monitor in animal husbandry.
文摘A modified separation method has been developed for determinating polychlorinated biphenyl congeners in environmental samples. Direct treatment of extract with concentrated HzSO4 was employed in the first step for removal of lipids and other interfering substances, then a joint column of alumina-silica gel(Ag+) was applied to separate PCBs fraction from HCH, DDT and its analogs. After this separation, the PCBs fraction was analyzed by capillary gas chromatography with ECD detector and confirmed by GC/MS. The recoveries of individual congeners in Aroclor 1254 through the separation are about 79%-84%. The method is very efficient and useful for determination of trace amount of PCB congeners in environmental samples.
