This paper proposed a semi-supervised regression model with co-training algorithm based on support vector machine, which was used for retrieving water quality variables from SPOT 5 remote sensing data. The model consi...This paper proposed a semi-supervised regression model with co-training algorithm based on support vector machine, which was used for retrieving water quality variables from SPOT 5 remote sensing data. The model consisted of two support vector regressors (SVRs). Nonlinear relationship between water quality variables and SPOT 5 spectrum was described by the two SVRs, and semi-supervised co-training algorithm for the SVRs was es-tablished. The model was used for retrieving concentrations of four representative pollution indicators―permangan- ate index (CODmn), ammonia nitrogen (NH3-N), chemical oxygen demand (COD) and dissolved oxygen (DO) of the Weihe River in Shaanxi Province, China. The spatial distribution map for those variables over a part of the Weihe River was also produced. SVR can be used to implement any nonlinear mapping readily, and semi-supervis- ed learning can make use of both labeled and unlabeled samples. By integrating the two SVRs and using semi-supervised learning, we provide an operational method when paired samples are limited. The results show that it is much better than the multiple statistical regression method, and can provide the whole water pollution condi-tions for management fast and can be extended to hyperspectral remote sensing applications.展开更多
In this paper, the principle to determine the atmospheric columnar Mie optical depth from downward total solar radiative flux is theoretically studied, and the effect on Mie optical depth solution of the errors in sur...In this paper, the principle to determine the atmospheric columnar Mie optical depth from downward total solar radiative flux is theoretically studied, and the effect on Mie optical depth solution of the errors in surface albedo, sin-gle scattering albedo, asymmetrical factor of scattering phase function, instrumental constant and the approximate expression of diffusion flux is analy/ed, and then a method for determining surface albedo in shorter wavelength range is presented.展开更多
Considering about the effect of whitecaps and foams on pulse-limited Radar Altimeters, an improved algorithm of retrieving sea surface wind speed is proposed in this paper. Firstly, a four-layer dielectric model is es...Considering about the effect of whitecaps and foams on pulse-limited Radar Altimeters, an improved algorithm of retrieving sea surface wind speed is proposed in this paper. Firstly, a four-layer dielectric model is established in order to simulate an air-sea interface. Secondly, the microwave reflectivity of a sea surface covered by spray droplets and foams at 13.5 GHz is computed based on the established model. These computed results show that the effect of spray droplets and foams in high sea state conditions shall not be negligible on retrieving sea surface wind speed. Finally, compared with the analytical algorithms proposed by Zhao and some calculated results based on a three-layer dielectric model, an improved algorithm of retrieving sea surface wind speed is presented. At a high wind speed, the improved algorithm is in a better accord with some empirical algorithms such as Brown, Young ones and et al., and also in a good agreement with ZT and other algorithms at low wind speed. This new improved algorithm will be suitable not only for low wind speed retrieval, but also for high wind speed retrieval. Better accuracy and effectiveness of wind speed retrieval can also be obtained.展开更多
This paper aims to develop Machine Learning algorithms to classify electronic articles related to this phenomenon by retrieving information and topic modelling.The Methodology of this study is categorized into three p...This paper aims to develop Machine Learning algorithms to classify electronic articles related to this phenomenon by retrieving information and topic modelling.The Methodology of this study is categorized into three phases:the Text Classification Approach(TCA),the Proposed Algorithms Interpretation(PAI),andfinally,Information Retrieval Approach(IRA).The TCA reflects the text preprocessing pipeline called a clean corpus.The Global Vec-tors for Word Representation(Glove)pre-trained model,FastText,Term Frequency-Inverse Document Fre-quency(TF-IDF),and Bag-of-Words(BOW)for extracting the features have been interpreted in this research.The PAI manifests the Bidirectional Long Short-Term Memory(Bi-LSTM)and Convolutional Neural Network(CNN)to classify the COVID-19 news.Again,the IRA explains the mathematical interpretation of Latent Dirich-let Allocation(LDA),obtained for modelling the topic of Information Retrieval(IR).In this study,99%accuracy was obtained by performing K-fold cross-validation on Bi-LSTM with Glove.A comparative analysis between Deep Learning and Machine Learning based on feature extraction and computational complexity exploration has been performed in this research.Furthermore,some text analyses and the most influential aspects of each document have been explored in this study.We have utilized Bidirectional Encoder Representations from Trans-formers(BERT)as a Deep Learning mechanism in our model training,but the result has not been uncovered satisfactory.However,the proposed system can be adjustable in the real-time news classification of COVID-19.展开更多
Back propagation neural networks are used to retrieve atmospheric temperature profiles from NOAA-16 Advanced Microwave Sounding Unit-A (AMSU-A) measurements over East Asia. The collocated radiosonde observation and AM...Back propagation neural networks are used to retrieve atmospheric temperature profiles from NOAA-16 Advanced Microwave Sounding Unit-A (AMSU-A) measurements over East Asia. The collocated radiosonde observation and AMSU-A data over land in 2002-2003 are used to train the network, and the data over land in 2004 are used to test the network. A comparison with the multi-linear regression method shows that the neural network retrieval method can significantly improve the results in all weather conditions. When an offset of 0.5 K or a noise level of ±0.2 K is added to all channels simultaneously, the increase in the overall root mean square (RMS) error is less than 0.1 K. Furthermore, an experiment is conducted to investigate the effects of the window channels on the retrieval. The results indicate that the brightness temperatures of window channels can provide significantly useful information on the temperature retrieval near the surface. Additionally, the RMS errors of the profiles retrieved with the trained neural network are compared with the errors from the International Advanced TOVS (ATOVS) Processing Package (IAPP). It is shown that the network-based algorithm can provide much better results in the experiment region and comparable results in other regions. It is also noted that the network can yield remarkably better results than IAPP at the low levels and at about the 250-hPa level in summer skies over ocean. Finally, the network-based retrieval algorithm developed herein is applied in retrieving the temperature anomalies of Typhoon Rananim from AMSU-A data.展开更多
A method to retrieve ocean wave spectra from SAR images, named Parameterized First-guess Spectrum Method （PFSM）, was proposed after interpretation of the theory to ocean wave imaging and analysis of the drawbacks of...A method to retrieve ocean wave spectra from SAR images, named Parameterized First-guess Spectrum Method （PFSM）, was proposed after interpretation of the theory to ocean wave imaging and analysis of the drawbacks of the retrieving model generally used. In this method, with additional information and satellite parameters, the separating wave-number is first calculated to determine the maximum wave-number beyond which the linear relation can be used. The separating wave-number can be calculated using the additional information on wind velocity and parameters of SAR satellite. And then the SAR spectrum can be divided into SAR spectrum of wind wave and of swell according to the result of separating wave-number. The portion of SAR spectrum generated by wind wave, is used to search for the most suitable parameters of ocean wind wave spectrum, including propagation direction of ocean wave, phase speed of dominating wave and the angle spreading coefficient. The swell spectrum is acquired by directly inversing the linear relation of ocean wave spectrum to SAR spectrum given the portion of SAR spectrum generated by swell. We used the proposed method to retrieve the ocean wave spectrum from ERS-SAR data from the South China Sea and compared the result with altimeter data. The agreement indicates that the PFSM is reliable.展开更多
Establishing the remote sensing algorithm of retrieving the absorption coefficient of seawater petroleum substances is an efficient way to improve the accuracy of retrieving a seawater petroleum concentration using a ...Establishing the remote sensing algorithm of retrieving the absorption coefficient of seawater petroleum substances is an efficient way to improve the accuracy of retrieving a seawater petroleum concentration using a remote sensing technology. A remote sensing reflectance is a basic physical parameter in water color remote sensing. Apply it to directly retrieve the absorption coefficient of seawater petroleum substances is of potential advantage. The absorption coefficient of waters containing petroleum [ACWCP, a_o（λ）], consists of the absorption coefficient of pure water [ACPW, a_w（λ）], plankton [ACP, a_（ph）（λ）], colored scraps [ACCS, a_（d,g）（λ）], and petroleum substance [ACPS, a_（oil）（λ）]. Among those, ACCS consists of the absorption coefficient of nonalgal particle [ACNP, a_d（λ）] and colored dissolved organic matter [ACCDOM, a_g（λ）]. For waters containing petroleum, the retrieved ACCS using the existing method is a combination absorption coefficient of ACNP,ACCDOM and ACPA [CAC, a_（d,g,oil）（λ）]. Therefore, the principle question is how to extract ACPS from CAC.Through the analysis of the three proportion tests conducted between the year of 2013 and 2015 and the corresponding remote sensing data, an algorithm of retrieving the absorption coefficient of petroleum substances is proposed based on remote sensing reflectance. First of all, ACPS and CAC are retrieved from the reflectance using the quasi-analytical algorithm（QAA）, with some parameter modified. Secondly, given the fact that the backscatter coefficient [BC, b_（bp）（555）] of total particles at 555 nm can be obtained completely from the reflectance, the relation between BC and ACNP in petroleum contaminated water can be established. As a result, ACNP can be calculated. Then, combining the remote sensing retrieving algorithm of a_g（440）, the method of achieving the spectral slope of the absorption coefficient can be established, from which ACCDOM,can be calculated. Finally, ACPS can be computed as the residual. The accuracy of ACPS based on this algorithm is 86% compared with the in situ measurements.展开更多
The visible and infrared bands of Landsat Thematic Mapper （TM） can be used for inland water studies. A method of retrieving water-leaving radiance from TM image over Taihu Lake in Jiangsu Province of China was inves...The visible and infrared bands of Landsat Thematic Mapper （TM） can be used for inland water studies. A method of retrieving water-leaving radiance from TM image over Taihu Lake in Jiangsu Province of China was investigated in this article. To estimate water-leaving radiance, atmospheric correction was performed in three visible bands of 485nm, 560nm and 660rim. Rayleigh scattering was computed precisely, and the aerosol contribution was estimated by adopting the clear-water-pixels approach. The clear waters were identified by using the Landsat TM middle-infrared band （2.1 μm）, and the water-leaving radiance of clear water pixels in the green band was estimated by using field data. Aerosol scattering at green band was derived for six points, and interpolated to match the TM image. Assuming the atmospheric correction coefficient was 1.0, the aerosol scattering image at blue and red bands were derived. Based on a simplified atmospheric radiation transfer model, the water-leaving radiance for three visible bands was retrieved. The water-leaving radiance was normalized to make it comparable with that estimated from other remotely sensed data acquired at different times, and under different atmospheric conditions. Additionally, remotely sensed reflectance of water was computed. To evaluate the atmospheric correction method presented in this article, the correlation was analyzed between the corrected remotely sensed data and the measured water parameters based on the retrieval model. The results show that the atmospheric correction method based on the image itself is more effective for the retrieval of water parameters from Landsat TM data than 6S （Second Simulation of the Satellite Signal in the Solar Spectrum） code based on standard atmospheric and aerosol models.展开更多
This paper introduces an algorithm for beamforming systems by the aid of multidimensional harmonic retrieval(MHR).This algorithm resolves problems,removes limitations of sampling and provides a more robust beamformer....This paper introduces an algorithm for beamforming systems by the aid of multidimensional harmonic retrieval(MHR).This algorithm resolves problems,removes limitations of sampling and provides a more robust beamformer.A new sample space is created that can be used for estimating weights of a new beamforming called spatial-harmonics retrieval beamformer(SHRB).Simulation results show that SHRB has a better performance,accuracy,and applicability and more powerful eigenvalues than conventional beamformers.A simple mathematical proof is provided.By changing the number of harmonics,as a degree of freedom that is missing in conventional beamformers,SHRB can achieve more optimal outputs without increasing the number of spatial or temporal samples.We will demonstrate that SHRB offers an improvement of 4 dB in signal to noise ratio(SNR) in bit error rate(BER) of 10~(-4) over conventional beamformers.In the case of direction of arrival(DOA) estimation,SHRB can estimate the DOA of the desired signal with an SNR of-25 dB,when conventional methods cannot have acceptable response.展开更多
A simple linear regression method is developed to retrieve daily averaged soil water content from diurnal variations of soil temperature measured at three or more depths. The method is applied to Oklahoma Mesonet soil...A simple linear regression method is developed to retrieve daily averaged soil water content from diurnal variations of soil temperature measured at three or more depths. The method is applied to Oklahoma Mesonet soil temperature data collected at the depths of 5, 10, and 30 cm during 11–20 June 1995. The retrieved bulk soil water contents are compared with direct measurements for one pair of nearly collocated Mesonet and ARM stations and also compared with the retrievals of a previous method at 14 enhanced Oklahoma Mesonet stations. The results show that the current method gives more persistent retrievals than the previous method. The method is also applied to Oklahoma Mesonet soil temperature data collected at the depths of 5, 25, 60, and 75 cm from the Norman site during 20–30 July 1998 and 1–31 July 2000. The retrieved soil water contents are verified by collocated soil water content measurements with rms differences smaller than the soil water observation error (0.05 m<SUP>3</SUP> m<SUP>−3</SUP>). The retrievals are found to be moderately sensitive to random errors (±0.1 K) in the soil temperature observations and errors in the soil type specifications.展开更多
In this study,we derived atmospheric profiles of temperature,moisture,and ozone,along with surface emissivity,skin temperature,and surface pressure,from infrared-sounder radiances under clear sky (cloudless) condition...In this study,we derived atmospheric profiles of temperature,moisture,and ozone,along with surface emissivity,skin temperature,and surface pressure,from infrared-sounder radiances under clear sky (cloudless) condition.Clouds were detected objectively using the Atmospheric Infrared Sounder under a relatively low spatial resolution and cloud-mask information from the Moderate Resolution Imaging Spectroradiometer under a high horizontal resolution;this detection was conducted using space matching.Newton’s nonlinear physical iterative solution technique is applied to the radiative transfer equation (RTE) to retrieve temperature profiles,relative humidity profiles,and surface variables simultaneously.This technique is carried out by using the results of an eigenvector regression retrieval as the background profile and using corresponding iterative forms for the weighting functions of temperature and water-vapor mixing ratio.The iterative forms are obtained by applying the variational principle to the RTE.We also compared the retrievals obtained with different types of observations.The results show that the retrieved atmospheric sounding profile has great superiority over other observations by accuracy and resolution.Retrieved profiles can be used to improve the initial conditions of numerical models and used in areas where conventional observations are sparse,such as plateaus,deserts,and seas.展开更多
The World Wide Web (WWW) has greatly changed the way of component based software reuse, for large number of components provided by different vendors become available and it's rather difficult to find and choose w...The World Wide Web (WWW) has greatly changed the way of component based software reuse, for large number of components provided by different vendors become available and it's rather difficult to find and choose what we in fact need. To make large amount of the components collaborate, an information exchanging model is essential. In order to retrieve and search the suitable or usable components more effectively, some techniques should be taken into account. Among these techniques, matching strategies and fuzzy URL semantics are significant for the former help us to find components which could be reused and the other both to broaden the searching areas and use some uncertain information to make the searching more purposive. A brief discuss on an abstract component model (UACModel) is begun, which was proposed to promote the interoperability and information exchange among various reusable component libraries (RCLs), and a framework for component retrieval. Then the emphases are put on some matching strategies, especially incomplete ones that encourage reuse through component customization, and fuzzy URL extensions to be supported and realized.展开更多
The paper develops a passive sub-millimeter precipitation retrievals algorithm for Microwave Humidity and Temperature Sounder(MWHTS)onboard the Chinese Feng Yun 3C(FY-3C)satellite.The retrieval algorithm employs a num...The paper develops a passive sub-millimeter precipitation retrievals algorithm for Microwave Humidity and Temperature Sounder(MWHTS)onboard the Chinese Feng Yun 3C(FY-3C)satellite.The retrieval algorithm employs a number of neural network estimators trained and evaluated using the validated global reference physical model NCEP/WRF/ARTS,and works for seawater.NCEP data per 6 hours are downloaded to run the Weather Research and Forecast model WRF,and derive the typical precipitation data from the whole world.The Atmospheric Radiative Transfer Simulator ARTS is feasible for performing simulations of atmospheric radiative transfer.Rain detection algorithm has been used to generate level 2 products.Retrievals are reliable for surface precipitation rate higher than 0.1 mm/h at 15km resolution,which is in good agreement with those retrieved using the Precipitation retrieval algorithm version 1(ATMP-1)for Advanced Technology Microwave Sounder(ATMS)aboard Suomi NPP satellite.展开更多
For a given incidence angle at the snow surface, a greater snow density causes a greater change in the incidence angle at the snow-ground interface; for a given snow density, however, a larger incidence angle at the s...For a given incidence angle at the snow surface, a greater snow density causes a greater change in the incidence angle at the snow-ground interface; for a given snow density, however, a larger incidence angle at the snow surface results in a greater change in the refractive angle in the snow layer, by comparing the difference of incidence angle at the snow-ground interface and the air-snow interface with different snow density. Algorithm for estimating dry snow density used backscattering measurements with polarimetric SAR at L-band frequency is developed based on simulation of the surface backscattering components ghh,and gvv using the IEM model and regression analysis. The comparison of the estimated snow density from SAR L-band images with that from field measurements during the SIR-C/X-SAR overpass shows root means square error of 0.050 g/cm3. It shows that this algorithm can be accurately used to estimate dry snow density distribution.展开更多
Image-based similar trademark retrieval is a time-consuming and labor-intensive task in the trademark examination process.This paper aims to support trademark examiners by training Deep Convolutional Neural Network(DC...Image-based similar trademark retrieval is a time-consuming and labor-intensive task in the trademark examination process.This paper aims to support trademark examiners by training Deep Convolutional Neural Network(DCNN)models for effective Trademark Image Retrieval(TIR).To achieve this goal,we first develop a novel labeling method that automatically generates hundreds of thousands of labeled similar and dissimilar trademark image pairs using accompanying data fields such as citation lists,Vienna classification(VC)codes,and trademark ownership information.This approach eliminates the need for manual labeling and provides a large-scale dataset suitable for training deep learning models.We then train DCNN models based on Siamese and Triplet architectures,evaluating various feature extractors to determine the most effective configuration.Furthermore,we present an Adapted Contrastive Loss Function(ACLF)for the trademark retrieval task,specifically engineered to mitigate the influence of noisy labels found in automatically created datasets.Experimental results indicate that our proposed model(Efficient-Net_v21_Siamese)performs best at both True Negative Rate(TNR)threshold levels,TNR 0.9 and TNR 0.95,with==respective True Positive Rates(TPRs)of 77.7%and 70.8%and accuracies of 83.9%and 80.4%.Additionally,when testing on the public trademark dataset METU_v2,our model achieves a normalized average rank(NAR)of 0.0169,outperforming the current state-of-the-art(SOTA)model.Based on these findings,we estimate that considering only approximately 10%of the returned trademarks would be sufficient,significantly reducing the review time.Therefore,the paper highlights the potential of utilizing national trademark data to enhance the accuracy and efficiency of trademark retrieval systems,ultimately supporting trademark examiners in their evaluation tasks.展开更多
Unknown geology ahead of the tunnel boring machine(TBM)brings a large safety risk for tunnel construction.Seismic ahead-prospecting using TBM drilling noise as a source can achieve near-real-time detection,meeting the...Unknown geology ahead of the tunnel boring machine(TBM)brings a large safety risk for tunnel construction.Seismic ahead-prospecting using TBM drilling noise as a source can achieve near-real-time detection,meeting the requirements of TBM rapid drilling.Seismic wavefield retrieval is the key data processing step for the efficient utilization of TBM drilling noise.The traditional solution is based on cross-correlation to extract reflected waves,but the reference waves remain in the result,disturbing the imaging and interpre-tation of the adverse geology.To solve this problem,the deep learning method was introduced in wavefield retrieval to improve the accu-racy of geological prospecting.We trained a deep neural network(DNN)with its strong nonlinear mapping capability to transform seismic data from TBM drilling noise to data from the active source.The issue lies in its features for this specific tunnel task,including the decay of the seismic signal with time and the incomplete spatial correspondence.Thus,we improved a classical DNN with the time constraint as an additional input,and an additional pre-decoder to enlarge the receptive field.Additionally,a loss function weighted by the ground truth and time constraint is improved to achieve an accurate retrieval of the effective signal,considering the little effective information in tunnel data.Finally,the workflow of the proposed method was given,and a dataset designed with reference to the field case was employed to train the network.The proposed method accurately retrieved the reflection signal with higher dominant frequen-cies,which helped improve the accuracy of imaging.Numerical simulations and imaging on typical geological models show that the pro-posed method can suppress reference waves and get more accurate results with fewer artifacts.The proposed method has been applied in the Gaoligongshan Tunnel and imaged two abnormal zones,providing meaningful geological information for TBM drilling and tunnel construction.展开更多
Pill image recognition is an important field in computer vision.It has become a vital technology in healthcare and pharmaceuticals due to the necessity for precise medication identification to prevent errors and ensur...Pill image recognition is an important field in computer vision.It has become a vital technology in healthcare and pharmaceuticals due to the necessity for precise medication identification to prevent errors and ensure patient safety.This survey examines the current state of pill image recognition,focusing on advancements,methodologies,and the challenges that remain unresolved.It provides a comprehensive overview of traditional image processing-based,machine learning-based,deep learning-based,and hybrid-based methods,and aims to explore the ongoing difficulties in the field.We summarize and classify the methods used in each article,compare the strengths and weaknesses of traditional image processing-based,machine learning-based,deep learning-based,and hybrid-based methods,and review benchmark datasets for pill image recognition.Additionally,we compare the performance of proposed methods on popular benchmark datasets.This survey applies recent advancements,such as Transformer models and cutting-edge technologies like Augmented Reality(AR),to discuss potential research directions and conclude the review.By offering a holistic perspective,this paper aims to serve as a valuable resource for researchers and practitioners striving to advance the field of pill image recognition.展开更多
This study describes the use of the weighted multiplicative algebraic reconstruction technique(WMART)to obtain vertical ozone profiles from limb observations performed by the scanning imaging absorption spectrometer f...This study describes the use of the weighted multiplicative algebraic reconstruction technique(WMART)to obtain vertical ozone profiles from limb observations performed by the scanning imaging absorption spectrometer for atmospheric chartography(SCIAMACHY).This technique is based on SaskMART(the combination of the multiplicative algebraic reconstruction technique and SaskTRAN radiative transfer model),which was originally developed for optical spectrometer and infrared imaging system(OSIRIS)data.One of the objectives of this study was to obtain consistent ozone profiles from the two satellites.In this study,the WMART algorithm is combined with a radiative transfer model(SCIATRAN),as well as a set of measurement vectors comprising five Hartley pairing vectors(HPVs)and one Chappuis triplet vector(CTV),to retrieve ozone profiles in the altitude range of 10–69 km.Considering that the weighting factors in WMART have a significant effect on the retrievals,we propose a novel approach to calculate the pair/triplet weighting factors using wavelength weighting functions.The results of the application of the proposed ozone retrieval scheme are compared with the SCIAMACHY v3.5 ozone product by University of Bremen and validated against profiles derived from other passive satellite observations or measured by ozonesondes.Between 18 and 55 km,the retrieved ozone profiles typically agree with data from the SCIAMACHY ozone product within 5%for tropics and middle latitudes,whereas a negative deviation exists between 35 and 50 km for northern high latitudes,with a deviation of less than 10%above 50 km.Comparison of the retrieved profiles with microwave limb sounder(MLS)v5.0 indicates that the difference is within±5%between 18 and 55 km,and an agreement within 10%is achieved in other altitudes for tropics and middle latitudes.Comparison of the retrieved profiles with OSIRIS v7.1 indicates that the average deviation is within±5%between 20 and 59 km,and difference of approximately 10%is achieved below 20 km.Compared with ozonesondes data,a general validity of the retrievals is no more than 5%between 15 and 30 km.展开更多
DDeeaarr EEddiittoorr,,The encoding and retrieval of emotional memories demands intricate interplay within the limbic network,where the network state is subject to significant reconfiguration by learning-induced plast...DDeeaarr EEddiittoorr,,The encoding and retrieval of emotional memories demands intricate interplay within the limbic network,where the network state is subject to significant reconfiguration by learning-induced plasticity,behavioral state,and contextual information[1].展开更多
Background:Testicular sperm aspiration(TESA)is a minimally invasive testicular sperm retrieval technique that has been utilized in the treatment of male factor infertility.We sought to evaluate sperm retrieval outcome...Background:Testicular sperm aspiration(TESA)is a minimally invasive testicular sperm retrieval technique that has been utilized in the treatment of male factor infertility.We sought to evaluate sperm retrieval outcomes of primary and redo TESA in men with severe oligoasthenoteratozoospermia(OAT)and obstructive azoospermia(OA).Methods:This is a retrospective analysis of consecutive TESAs(primary and redo)for men with severe OAT and OA performed between January 2011 and August 2022 at a high-volume infertility center.We compared TESA outcomes in men with severe OAT to those with OA and compared outcomes of men who underwent primary and redo TESA on the same testicular unit.Results:439 TESAs(366 primary and 73 redo)in men with severe OAT(n=133)and OA(n=306)were included.Men with OA had significantly higher sperm retrieval rate(SRR)and motile SRR compared to men with severe OAT(99%vs.95%and 98%vs.83%,respectively,p<0.05).The requirement for multiple biopsies and the total number of aspirates were significantly lower in men with OA compared to those with severe OAT(15%vs.32%and 1.2±0.5 vs.1.4±0.7,respectively,p<0.05).In both groups,SRR,motile SRR,the requirement for multiple biopsies,and the total number of aspirates were not significantly different in primary compared to redo cases.Conclusion:Our data demonstrate that TESA retrieval rates are significantly higher in men with OA compared to those with severe OAT.The data also demonstrate that a redo TESA in these men is as effective as a primary TESA,suggesting that areas of active spermatogenesis are preserved 6 months after TESA.展开更多
基金Under the auspices of National Natural Science Foundation of China (No. 40671133)Fundamental Research Funds for the Central Universities (No. GK200902015)
文摘This paper proposed a semi-supervised regression model with co-training algorithm based on support vector machine, which was used for retrieving water quality variables from SPOT 5 remote sensing data. The model consisted of two support vector regressors (SVRs). Nonlinear relationship between water quality variables and SPOT 5 spectrum was described by the two SVRs, and semi-supervised co-training algorithm for the SVRs was es-tablished. The model was used for retrieving concentrations of four representative pollution indicators―permangan- ate index (CODmn), ammonia nitrogen (NH3-N), chemical oxygen demand (COD) and dissolved oxygen (DO) of the Weihe River in Shaanxi Province, China. The spatial distribution map for those variables over a part of the Weihe River was also produced. SVR can be used to implement any nonlinear mapping readily, and semi-supervis- ed learning can make use of both labeled and unlabeled samples. By integrating the two SVRs and using semi-supervised learning, we provide an operational method when paired samples are limited. The results show that it is much better than the multiple statistical regression method, and can provide the whole water pollution condi-tions for management fast and can be extended to hyperspectral remote sensing applications.
文摘In this paper, the principle to determine the atmospheric columnar Mie optical depth from downward total solar radiative flux is theoretically studied, and the effect on Mie optical depth solution of the errors in surface albedo, sin-gle scattering albedo, asymmetrical factor of scattering phase function, instrumental constant and the approximate expression of diffusion flux is analy/ed, and then a method for determining surface albedo in shorter wavelength range is presented.
文摘Considering about the effect of whitecaps and foams on pulse-limited Radar Altimeters, an improved algorithm of retrieving sea surface wind speed is proposed in this paper. Firstly, a four-layer dielectric model is established in order to simulate an air-sea interface. Secondly, the microwave reflectivity of a sea surface covered by spray droplets and foams at 13.5 GHz is computed based on the established model. These computed results show that the effect of spray droplets and foams in high sea state conditions shall not be negligible on retrieving sea surface wind speed. Finally, compared with the analytical algorithms proposed by Zhao and some calculated results based on a three-layer dielectric model, an improved algorithm of retrieving sea surface wind speed is presented. At a high wind speed, the improved algorithm is in a better accord with some empirical algorithms such as Brown, Young ones and et al., and also in a good agreement with ZT and other algorithms at low wind speed. This new improved algorithm will be suitable not only for low wind speed retrieval, but also for high wind speed retrieval. Better accuracy and effectiveness of wind speed retrieval can also be obtained.
文摘This paper aims to develop Machine Learning algorithms to classify electronic articles related to this phenomenon by retrieving information and topic modelling.The Methodology of this study is categorized into three phases:the Text Classification Approach(TCA),the Proposed Algorithms Interpretation(PAI),andfinally,Information Retrieval Approach(IRA).The TCA reflects the text preprocessing pipeline called a clean corpus.The Global Vec-tors for Word Representation(Glove)pre-trained model,FastText,Term Frequency-Inverse Document Fre-quency(TF-IDF),and Bag-of-Words(BOW)for extracting the features have been interpreted in this research.The PAI manifests the Bidirectional Long Short-Term Memory(Bi-LSTM)and Convolutional Neural Network(CNN)to classify the COVID-19 news.Again,the IRA explains the mathematical interpretation of Latent Dirich-let Allocation(LDA),obtained for modelling the topic of Information Retrieval(IR).In this study,99%accuracy was obtained by performing K-fold cross-validation on Bi-LSTM with Glove.A comparative analysis between Deep Learning and Machine Learning based on feature extraction and computational complexity exploration has been performed in this research.Furthermore,some text analyses and the most influential aspects of each document have been explored in this study.We have utilized Bidirectional Encoder Representations from Trans-formers(BERT)as a Deep Learning mechanism in our model training,but the result has not been uncovered satisfactory.However,the proposed system can be adjustable in the real-time news classification of COVID-19.
文摘Back propagation neural networks are used to retrieve atmospheric temperature profiles from NOAA-16 Advanced Microwave Sounding Unit-A (AMSU-A) measurements over East Asia. The collocated radiosonde observation and AMSU-A data over land in 2002-2003 are used to train the network, and the data over land in 2004 are used to test the network. A comparison with the multi-linear regression method shows that the neural network retrieval method can significantly improve the results in all weather conditions. When an offset of 0.5 K or a noise level of ±0.2 K is added to all channels simultaneously, the increase in the overall root mean square (RMS) error is less than 0.1 K. Furthermore, an experiment is conducted to investigate the effects of the window channels on the retrieval. The results indicate that the brightness temperatures of window channels can provide significantly useful information on the temperature retrieval near the surface. Additionally, the RMS errors of the profiles retrieved with the trained neural network are compared with the errors from the International Advanced TOVS (ATOVS) Processing Package (IAPP). It is shown that the network-based algorithm can provide much better results in the experiment region and comparable results in other regions. It is also noted that the network can yield remarkably better results than IAPP at the low levels and at about the 250-hPa level in summer skies over ocean. Finally, the network-based retrieval algorithm developed herein is applied in retrieving the temperature anomalies of Typhoon Rananim from AMSU-A data.
基金Supported by the High-Tech Research and Development Program of China (863 Program, No. 2001AA633070 2003AA604040)the National Basic Research Program of China (973 Program. No. 2005CB422307)
文摘A method to retrieve ocean wave spectra from SAR images, named Parameterized First-guess Spectrum Method （PFSM）, was proposed after interpretation of the theory to ocean wave imaging and analysis of the drawbacks of the retrieving model generally used. In this method, with additional information and satellite parameters, the separating wave-number is first calculated to determine the maximum wave-number beyond which the linear relation can be used. The separating wave-number can be calculated using the additional information on wind velocity and parameters of SAR satellite. And then the SAR spectrum can be divided into SAR spectrum of wind wave and of swell according to the result of separating wave-number. The portion of SAR spectrum generated by wind wave, is used to search for the most suitable parameters of ocean wind wave spectrum, including propagation direction of ocean wave, phase speed of dominating wave and the angle spreading coefficient. The swell spectrum is acquired by directly inversing the linear relation of ocean wave spectrum to SAR spectrum given the portion of SAR spectrum generated by swell. We used the proposed method to retrieve the ocean wave spectrum from ERS-SAR data from the South China Sea and compared the result with altimeter data. The agreement indicates that the PFSM is reliable.
基金The National Natural Science Foundation of China under contract No.41271364the Key Projects in the National Science and Technology Pillar Program of China under contract No.2012BAH32B01-4the Program for Scientific Research Start-up Funds of Guangdong Ocean University under contract No.E16187
文摘Establishing the remote sensing algorithm of retrieving the absorption coefficient of seawater petroleum substances is an efficient way to improve the accuracy of retrieving a seawater petroleum concentration using a remote sensing technology. A remote sensing reflectance is a basic physical parameter in water color remote sensing. Apply it to directly retrieve the absorption coefficient of seawater petroleum substances is of potential advantage. The absorption coefficient of waters containing petroleum [ACWCP, a_o（λ）], consists of the absorption coefficient of pure water [ACPW, a_w（λ）], plankton [ACP, a_（ph）（λ）], colored scraps [ACCS, a_（d,g）（λ）], and petroleum substance [ACPS, a_（oil）（λ）]. Among those, ACCS consists of the absorption coefficient of nonalgal particle [ACNP, a_d（λ）] and colored dissolved organic matter [ACCDOM, a_g（λ）]. For waters containing petroleum, the retrieved ACCS using the existing method is a combination absorption coefficient of ACNP,ACCDOM and ACPA [CAC, a_（d,g,oil）（λ）]. Therefore, the principle question is how to extract ACPS from CAC.Through the analysis of the three proportion tests conducted between the year of 2013 and 2015 and the corresponding remote sensing data, an algorithm of retrieving the absorption coefficient of petroleum substances is proposed based on remote sensing reflectance. First of all, ACPS and CAC are retrieved from the reflectance using the quasi-analytical algorithm（QAA）, with some parameter modified. Secondly, given the fact that the backscatter coefficient [BC, b_（bp）（555）] of total particles at 555 nm can be obtained completely from the reflectance, the relation between BC and ACNP in petroleum contaminated water can be established. As a result, ACNP can be calculated. Then, combining the remote sensing retrieving algorithm of a_g（440）, the method of achieving the spectral slope of the absorption coefficient can be established, from which ACCDOM,can be calculated. Finally, ACPS can be computed as the residual. The accuracy of ACPS based on this algorithm is 86% compared with the in situ measurements.
基金Under the auspices of National Natural Science Foundation of China (No. 40671138)
文摘The visible and infrared bands of Landsat Thematic Mapper （TM） can be used for inland water studies. A method of retrieving water-leaving radiance from TM image over Taihu Lake in Jiangsu Province of China was investigated in this article. To estimate water-leaving radiance, atmospheric correction was performed in three visible bands of 485nm, 560nm and 660rim. Rayleigh scattering was computed precisely, and the aerosol contribution was estimated by adopting the clear-water-pixels approach. The clear waters were identified by using the Landsat TM middle-infrared band （2.1 μm）, and the water-leaving radiance of clear water pixels in the green band was estimated by using field data. Aerosol scattering at green band was derived for six points, and interpolated to match the TM image. Assuming the atmospheric correction coefficient was 1.0, the aerosol scattering image at blue and red bands were derived. Based on a simplified atmospheric radiation transfer model, the water-leaving radiance for three visible bands was retrieved. The water-leaving radiance was normalized to make it comparable with that estimated from other remotely sensed data acquired at different times, and under different atmospheric conditions. Additionally, remotely sensed reflectance of water was computed. To evaluate the atmospheric correction method presented in this article, the correlation was analyzed between the corrected remotely sensed data and the measured water parameters based on the retrieval model. The results show that the atmospheric correction method based on the image itself is more effective for the retrieval of water parameters from Landsat TM data than 6S （Second Simulation of the Satellite Signal in the Solar Spectrum） code based on standard atmospheric and aerosol models.
文摘This paper introduces an algorithm for beamforming systems by the aid of multidimensional harmonic retrieval(MHR).This algorithm resolves problems,removes limitations of sampling and provides a more robust beamformer.A new sample space is created that can be used for estimating weights of a new beamforming called spatial-harmonics retrieval beamformer(SHRB).Simulation results show that SHRB has a better performance,accuracy,and applicability and more powerful eigenvalues than conventional beamformers.A simple mathematical proof is provided.By changing the number of harmonics,as a degree of freedom that is missing in conventional beamformers,SHRB can achieve more optimal outputs without increasing the number of spatial or temporal samples.We will demonstrate that SHRB offers an improvement of 4 dB in signal to noise ratio(SNR) in bit error rate(BER) of 10~(-4) over conventional beamformers.In the case of direction of arrival(DOA) estimation,SHRB can estimate the DOA of the desired signal with an SNR of-25 dB,when conventional methods cannot have acceptable response.
文摘A simple linear regression method is developed to retrieve daily averaged soil water content from diurnal variations of soil temperature measured at three or more depths. The method is applied to Oklahoma Mesonet soil temperature data collected at the depths of 5, 10, and 30 cm during 11–20 June 1995. The retrieved bulk soil water contents are compared with direct measurements for one pair of nearly collocated Mesonet and ARM stations and also compared with the retrievals of a previous method at 14 enhanced Oklahoma Mesonet stations. The results show that the current method gives more persistent retrievals than the previous method. The method is also applied to Oklahoma Mesonet soil temperature data collected at the depths of 5, 25, 60, and 75 cm from the Norman site during 20–30 July 1998 and 1–31 July 2000. The retrieved soil water contents are verified by collocated soil water content measurements with rms differences smaller than the soil water observation error (0.05 m<SUP>3</SUP> m<SUP>−3</SUP>). The retrievals are found to be moderately sensitive to random errors (±0.1 K) in the soil temperature observations and errors in the soil type specifications.
基金project of the Ministry of Sciences and Technology of the People’s Republic of China (GYHY200706020)projects of National Natural Science Foundation of China ((40975034, 40505009)project of State Key Laboratory of Severe Weather (2008LASW-A01)
文摘In this study,we derived atmospheric profiles of temperature,moisture,and ozone,along with surface emissivity,skin temperature,and surface pressure,from infrared-sounder radiances under clear sky (cloudless) condition.Clouds were detected objectively using the Atmospheric Infrared Sounder under a relatively low spatial resolution and cloud-mask information from the Moderate Resolution Imaging Spectroradiometer under a high horizontal resolution;this detection was conducted using space matching.Newton’s nonlinear physical iterative solution technique is applied to the radiative transfer equation (RTE) to retrieve temperature profiles,relative humidity profiles,and surface variables simultaneously.This technique is carried out by using the results of an eigenvector regression retrieval as the background profile and using corresponding iterative forms for the weighting functions of temperature and water-vapor mixing ratio.The iterative forms are obtained by applying the variational principle to the RTE.We also compared the retrievals obtained with different types of observations.The results show that the retrieved atmospheric sounding profile has great superiority over other observations by accuracy and resolution.Retrieved profiles can be used to improve the initial conditions of numerical models and used in areas where conventional observations are sparse,such as plateaus,deserts,and seas.
基金Supported by Visiting Scholar Foundation of Key L ab In University
文摘The World Wide Web (WWW) has greatly changed the way of component based software reuse, for large number of components provided by different vendors become available and it's rather difficult to find and choose what we in fact need. To make large amount of the components collaborate, an information exchanging model is essential. In order to retrieve and search the suitable or usable components more effectively, some techniques should be taken into account. Among these techniques, matching strategies and fuzzy URL semantics are significant for the former help us to find components which could be reused and the other both to broaden the searching areas and use some uncertain information to make the searching more purposive. A brief discuss on an abstract component model (UACModel) is begun, which was proposed to promote the interoperability and information exchange among various reusable component libraries (RCLs), and a framework for component retrieval. Then the emphases are put on some matching strategies, especially incomplete ones that encourage reuse through component customization, and fuzzy URL extensions to be supported and realized.
文摘The paper develops a passive sub-millimeter precipitation retrievals algorithm for Microwave Humidity and Temperature Sounder(MWHTS)onboard the Chinese Feng Yun 3C(FY-3C)satellite.The retrieval algorithm employs a number of neural network estimators trained and evaluated using the validated global reference physical model NCEP/WRF/ARTS,and works for seawater.NCEP data per 6 hours are downloaded to run the Weather Research and Forecast model WRF,and derive the typical precipitation data from the whole world.The Atmospheric Radiative Transfer Simulator ARTS is feasible for performing simulations of atmospheric radiative transfer.Rain detection algorithm has been used to generate level 2 products.Retrievals are reliable for surface precipitation rate higher than 0.1 mm/h at 15km resolution,which is in good agreement with those retrieved using the Precipitation retrieval algorithm version 1(ATMP-1)for Advanced Technology Microwave Sounder(ATMS)aboard Suomi NPP satellite.
基金This work was supported by the Key Program of the Chinese Academy of Sciences (Grant Nos. KZ95T-03 and KZCX2-703) the National Natural Science Foundation of China (Grant Nos. 40001015 and 49989001) and the National Key Basic Research Program (Grant N
文摘For a given incidence angle at the snow surface, a greater snow density causes a greater change in the incidence angle at the snow-ground interface; for a given snow density, however, a larger incidence angle at the snow surface results in a greater change in the refractive angle in the snow layer, by comparing the difference of incidence angle at the snow-ground interface and the air-snow interface with different snow density. Algorithm for estimating dry snow density used backscattering measurements with polarimetric SAR at L-band frequency is developed based on simulation of the surface backscattering components ghh,and gvv using the IEM model and regression analysis. The comparison of the estimated snow density from SAR L-band images with that from field measurements during the SIR-C/X-SAR overpass shows root means square error of 0.050 g/cm3. It shows that this algorithm can be accurately used to estimate dry snow density distribution.
基金funded by the Institute of InformationTechnology,VietnamAcademy of Science and Technology(project number CSCL02.02/22-23)“Research and Development of Methods for Searching Similar Trademark Images Using Machine Learning to Support Trademark Examination in Vietnam”.
文摘Image-based similar trademark retrieval is a time-consuming and labor-intensive task in the trademark examination process.This paper aims to support trademark examiners by training Deep Convolutional Neural Network(DCNN)models for effective Trademark Image Retrieval(TIR).To achieve this goal,we first develop a novel labeling method that automatically generates hundreds of thousands of labeled similar and dissimilar trademark image pairs using accompanying data fields such as citation lists,Vienna classification(VC)codes,and trademark ownership information.This approach eliminates the need for manual labeling and provides a large-scale dataset suitable for training deep learning models.We then train DCNN models based on Siamese and Triplet architectures,evaluating various feature extractors to determine the most effective configuration.Furthermore,we present an Adapted Contrastive Loss Function(ACLF)for the trademark retrieval task,specifically engineered to mitigate the influence of noisy labels found in automatically created datasets.Experimental results indicate that our proposed model(Efficient-Net_v21_Siamese)performs best at both True Negative Rate(TNR)threshold levels,TNR 0.9 and TNR 0.95,with==respective True Positive Rates(TPRs)of 77.7%and 70.8%and accuracies of 83.9%and 80.4%.Additionally,when testing on the public trademark dataset METU_v2,our model achieves a normalized average rank(NAR)of 0.0169,outperforming the current state-of-the-art(SOTA)model.Based on these findings,we estimate that considering only approximately 10%of the returned trademarks would be sufficient,significantly reducing the review time.Therefore,the paper highlights the potential of utilizing national trademark data to enhance the accuracy and efficiency of trademark retrieval systems,ultimately supporting trademark examiners in their evaluation tasks.
基金supported by the National Natural Science Foundation of China(Grant No.42107165)Young Elite Scientist Sponsorship Program by Cast of China Association for Science and Technology(Grant No.YESS20210144)+1 种基金Shandong Provincial Natural Science Foundation of China(Grant No.ZR2021QE242)Science&Technology Program of Department of Transport of Shandong Province,China(Grant No.2019B47_2).
文摘Unknown geology ahead of the tunnel boring machine(TBM)brings a large safety risk for tunnel construction.Seismic ahead-prospecting using TBM drilling noise as a source can achieve near-real-time detection,meeting the requirements of TBM rapid drilling.Seismic wavefield retrieval is the key data processing step for the efficient utilization of TBM drilling noise.The traditional solution is based on cross-correlation to extract reflected waves,but the reference waves remain in the result,disturbing the imaging and interpre-tation of the adverse geology.To solve this problem,the deep learning method was introduced in wavefield retrieval to improve the accu-racy of geological prospecting.We trained a deep neural network(DNN)with its strong nonlinear mapping capability to transform seismic data from TBM drilling noise to data from the active source.The issue lies in its features for this specific tunnel task,including the decay of the seismic signal with time and the incomplete spatial correspondence.Thus,we improved a classical DNN with the time constraint as an additional input,and an additional pre-decoder to enlarge the receptive field.Additionally,a loss function weighted by the ground truth and time constraint is improved to achieve an accurate retrieval of the effective signal,considering the little effective information in tunnel data.Finally,the workflow of the proposed method was given,and a dataset designed with reference to the field case was employed to train the network.The proposed method accurately retrieved the reflection signal with higher dominant frequen-cies,which helped improve the accuracy of imaging.Numerical simulations and imaging on typical geological models show that the pro-posed method can suppress reference waves and get more accurate results with fewer artifacts.The proposed method has been applied in the Gaoligongshan Tunnel and imaged two abnormal zones,providing meaningful geological information for TBM drilling and tunnel construction.
文摘Pill image recognition is an important field in computer vision.It has become a vital technology in healthcare and pharmaceuticals due to the necessity for precise medication identification to prevent errors and ensure patient safety.This survey examines the current state of pill image recognition,focusing on advancements,methodologies,and the challenges that remain unresolved.It provides a comprehensive overview of traditional image processing-based,machine learning-based,deep learning-based,and hybrid-based methods,and aims to explore the ongoing difficulties in the field.We summarize and classify the methods used in each article,compare the strengths and weaknesses of traditional image processing-based,machine learning-based,deep learning-based,and hybrid-based methods,and review benchmark datasets for pill image recognition.Additionally,we compare the performance of proposed methods on popular benchmark datasets.This survey applies recent advancements,such as Transformer models and cutting-edge technologies like Augmented Reality(AR),to discuss potential research directions and conclude the review.By offering a holistic perspective,this paper aims to serve as a valuable resource for researchers and practitioners striving to advance the field of pill image recognition.
基金supported by the National Science Foundations of China(No.61905256)the National Key Research and Development Program of China(No.2019YFC0214702)the Youth Innovation Promotion Association of Chinese Academy of Sciences(No.2020439)。
文摘This study describes the use of the weighted multiplicative algebraic reconstruction technique(WMART)to obtain vertical ozone profiles from limb observations performed by the scanning imaging absorption spectrometer for atmospheric chartography(SCIAMACHY).This technique is based on SaskMART(the combination of the multiplicative algebraic reconstruction technique and SaskTRAN radiative transfer model),which was originally developed for optical spectrometer and infrared imaging system(OSIRIS)data.One of the objectives of this study was to obtain consistent ozone profiles from the two satellites.In this study,the WMART algorithm is combined with a radiative transfer model(SCIATRAN),as well as a set of measurement vectors comprising five Hartley pairing vectors(HPVs)and one Chappuis triplet vector(CTV),to retrieve ozone profiles in the altitude range of 10–69 km.Considering that the weighting factors in WMART have a significant effect on the retrievals,we propose a novel approach to calculate the pair/triplet weighting factors using wavelength weighting functions.The results of the application of the proposed ozone retrieval scheme are compared with the SCIAMACHY v3.5 ozone product by University of Bremen and validated against profiles derived from other passive satellite observations or measured by ozonesondes.Between 18 and 55 km,the retrieved ozone profiles typically agree with data from the SCIAMACHY ozone product within 5%for tropics and middle latitudes,whereas a negative deviation exists between 35 and 50 km for northern high latitudes,with a deviation of less than 10%above 50 km.Comparison of the retrieved profiles with microwave limb sounder(MLS)v5.0 indicates that the difference is within±5%between 18 and 55 km,and an agreement within 10%is achieved in other altitudes for tropics and middle latitudes.Comparison of the retrieved profiles with OSIRIS v7.1 indicates that the average deviation is within±5%between 20 and 59 km,and difference of approximately 10%is achieved below 20 km.Compared with ozonesondes data,a general validity of the retrievals is no more than 5%between 15 and 30 km.
基金supported by the National Natural Science Foundation of China(T2394531)the National Key R&D Program of China(2024YFF1206500)+1 种基金the Shanghai Municipal Science and Technology Major Project(2018SHZDZX01)ZJ Lab,and the Shanghai Center for Brain Science and Brain-Inspired Technology,China.
文摘DDeeaarr EEddiittoorr,,The encoding and retrieval of emotional memories demands intricate interplay within the limbic network,where the network state is subject to significant reconfiguration by learning-induced plasticity,behavioral state,and contextual information[1].
文摘Background:Testicular sperm aspiration(TESA)is a minimally invasive testicular sperm retrieval technique that has been utilized in the treatment of male factor infertility.We sought to evaluate sperm retrieval outcomes of primary and redo TESA in men with severe oligoasthenoteratozoospermia(OAT)and obstructive azoospermia(OA).Methods:This is a retrospective analysis of consecutive TESAs(primary and redo)for men with severe OAT and OA performed between January 2011 and August 2022 at a high-volume infertility center.We compared TESA outcomes in men with severe OAT to those with OA and compared outcomes of men who underwent primary and redo TESA on the same testicular unit.Results:439 TESAs(366 primary and 73 redo)in men with severe OAT(n=133)and OA(n=306)were included.Men with OA had significantly higher sperm retrieval rate(SRR)and motile SRR compared to men with severe OAT(99%vs.95%and 98%vs.83%,respectively,p<0.05).The requirement for multiple biopsies and the total number of aspirates were significantly lower in men with OA compared to those with severe OAT(15%vs.32%and 1.2±0.5 vs.1.4±0.7,respectively,p<0.05).In both groups,SRR,motile SRR,the requirement for multiple biopsies,and the total number of aspirates were not significantly different in primary compared to redo cases.Conclusion:Our data demonstrate that TESA retrieval rates are significantly higher in men with OA compared to those with severe OAT.The data also demonstrate that a redo TESA in these men is as effective as a primary TESA,suggesting that areas of active spermatogenesis are preserved 6 months after TESA.
