A method is developed to assess retrievability, namely the retrieval potential for atmospheric temperature profiles, from satellite infrared measurements in clear-sky conditions. This technique is based upon generaliz...A method is developed to assess retrievability, namely the retrieval potential for atmospheric temperature profiles, from satellite infrared measurements in clear-sky conditions. This technique is based upon generalized linear inverse theory and empirical orthogonal function analysis. Utilizing the NCEP global temperature reanalysis data in January and July from 1999 to 2003, the retrievabilities obtained with the Atmospheric Infrared Sounder （AIRS） and the High Resolution Infrared Radiation Sounder/3 （HIRS/3） sounding channel data are derived respectively for each standard pressure level on a global scale. As an incidental result of this study, the optimum truncation number in the method of generalized linear inverse is deduced too. The results show that the retrievabilities of temperature obtained with the two datasets are similar in spatial distribution and seasonal change characteristics. As for the vertical distribution, the retrievabilities are low in the upper and lower atmosphere, and high between 400 hPa and 850 hPa. For the geographical distribution, the retrievabilities are low in the low-latitude oceanic regions and in some regions in Antarctica, and relatively high in mid-high latitudes and continental regions. Compared with the HIRS/3 data, the retrievability obtained with the AIRS data can be improved by an amount between 0.15 and 0.40.展开更多
With the development of cloud storage,the problem of efficiently checking and proving data integrity needs more consideration.Therefore,much of growing interest has been pursed in the context of the integrity verifica...With the development of cloud storage,the problem of efficiently checking and proving data integrity needs more consideration.Therefore,much of growing interest has been pursed in the context of the integrity verification of cloud storage.Provable data possession(PDP)and Proofs of retrievablity(POR)are two kinds of important scheme which can guarantee the data integrity in the cloud storage environments.The main difference between them is that POR schemes store a redundant encoding of the client data on the server so as to she has the ability of retrievablity while PDP does not have.Unfortunately,most of POR schemes support only static data.Stefanov et al.proposed a dynamic POR,but their scheme need a large of amount of client storage and has a large audit cost.Cash et al.use Oblivious RAM(ORAM)to construct a fully dynamic POR scheme,but the cost of their scheme is also very heavy.Based on the idea which proposed by Cash,we propose dynamic proofs of retrievability via Partitioning-Based Square Root Oblivious RAM(DPoR-PSR-ORAM).Firstly,the notions used in our scheme are defined.The Partitioning-Based Square Root Oblivious RAM(PSR-ORAM)protocol is also proposed.The DPOR-PSR-ORAM Model which includes the formal definitions,security definitions and model construction methods are described in the paper.Finally,we give the security analysis and efficiency analysis.The analysis results show that our scheme not only has the property of correctness,authenticity,next-read pattern hiding and retrievabiltiy,but also has the high efficiency.展开更多
Data security is a significant issue in cloud storage systems. After outsourcing data to cloud servers, clients lose physical control over the data. To guarantee clients that their data is intact on the server side, s...Data security is a significant issue in cloud storage systems. After outsourcing data to cloud servers, clients lose physical control over the data. To guarantee clients that their data is intact on the server side, some mechanism is needed for clients to periodically check the integrity of their data. Proof of retrievability （PoR） is designed to ensure data integrity. However, most prior PoR schemes focus on static data, and existing dynamic PoR is inefficient. In this paper, we propose a new version of dynamic PoR that is based on a B＋ tree and a Merkle hash tree. We propose a novel authenticated data structure, called Cloud Merkle B＋ tree （CMBT）. By combining CMBT with the BES signature, dynamic operations such as insertion, deletion, and modification are supported. Compared with existing PoR schemes, our scheme improves worst-case overhead from O（n） to O（log n）.展开更多
Traceability and trustiness are two critical issues in the logistics sector.Blockchain provides a potential way for logistics tracking systems due to its traits of tamper resistance.However,it is non-trivial to apply ...Traceability and trustiness are two critical issues in the logistics sector.Blockchain provides a potential way for logistics tracking systems due to its traits of tamper resistance.However,it is non-trivial to apply blockchain on logistics because of firstly,the binding relationship between virtue data and physical location cannot be guaranteed so that frauds may exist.Secondly,it is neither practical to upload complete data on the blockchain due to the limited storage resources nor convincing to trust the digest of the data.This paper proposes a traceable and trustable consortium blockchain for logistics T^(2)L to provide an efficient solution to the mentioned problems.Specifically,the authenticated geocoding data from telecom operators’base stations are adopted to ensure the location credibility of the data before being uploaded to the blockchain for the purpose of reliable traceability of the logistics.Moreover,we propose a scheme based on Zero Knowledge Proof of Retrievability(ZK BLS-PoR)to ensure the trustiness of the data digest and the proofs to the blockchain.Any user in the system can check the data completeness by verifying the proofs instead of downloading and examining the whole data based on the proposed ZK BLS-PoR scheme,which can provide solid theoretical verification.In all,the proposed T^(2)L framework is a traceable and trustable logistics system with a high level of security.展开更多
In global navigation satellite system denial environment,cross-view geo-localization based on image retrieval presents an exceedingly critical visual localization solution for Unmanned Aerial Vehicle(UAV)systems.The e...In global navigation satellite system denial environment,cross-view geo-localization based on image retrieval presents an exceedingly critical visual localization solution for Unmanned Aerial Vehicle(UAV)systems.The essence of cross-view geo-localization resides in matching images containing the same geographical targets from disparate platforms,such as UAV-view and satellite-view images.However,images of the same geographical targets may suffer from occlusions and geometric distortions due to variations in the capturing platform,view,and timing.The existing methods predominantly extract features by segmenting feature maps,which overlook the holistic semantic distribution and structural information of objects,resulting in loss of image information.To address these challenges,dilated neighborhood attention Transformer is employed as the feature extraction backbone,and Multi-feature representations based on Multi-scale Hierarchical Contextual Aggregation(MMHCA)is proposed.In the proposed MMHCA method,the multiscale hierarchical contextual aggregation method is utilized to extract contextual information from local to global across various granularity levels,establishing feature associations of contextual information with global and local information in the image.Subsequently,the multi-feature representations method is utilized to obtain rich discriminative feature information,bolstering the robustness of model in scenarios characterized by positional shifts,varying distances,and scale ambiguities.Comprehensive experiments conducted on the extensively utilized University-1652 and SUES-200 benchmarks indicate that the MMHCA method surpasses the existing techniques.showing outstanding results in UAV localization and navigation.展开更多
Instrument separation is a critical complication during root canal therapy,impacting treatment success and long-term tooth preservation.The etiology of instrument separation is multifactorial,involving the intricate a...Instrument separation is a critical complication during root canal therapy,impacting treatment success and long-term tooth preservation.The etiology of instrument separation is multifactorial,involving the intricate anatomy of the root canal system,instrument-related factors,and instrumentation techniques.Instrument separation can hinder thorough cleaning,shaping,and obturation of the root canal,posing challenges to successful treatment outcomes.Although retrieval of separated instrument is often feasible,it carries risks including perforation,excessive removal of tooth structure and root fractures.Effective management of separated instruments requires a comprehensive understanding of the contributing factors,meticulous preoperative assessment,and precise evaluation of the retrieval difficulty.The application of appropriate retrieval techniques is essential to minimize complications and optimize clinical outcomes.The current manuscript provides a framework for understanding the causes,risk factors,and clinical management principles of instrument separation.By integrating effective strategies,endodontists can enhance decision-making,improve endodontic treatment success and ensure the preservation of natural dentition.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
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
Content-Based Image Retrieval(CBIR)and image mining are becoming more important study fields in computer vision due to their wide range of applications in healthcare,security,and various domains.The image retrieval sy...Content-Based Image Retrieval(CBIR)and image mining are becoming more important study fields in computer vision due to their wide range of applications in healthcare,security,and various domains.The image retrieval system mainly relies on the efficiency and accuracy of the classification models.This research addresses the challenge of enhancing the image retrieval system by developing a novel approach,EfficientNet-Convolutional Neural Network(EffNet-CNN).The key objective of this research is to evaluate the proposed EffNet-CNN model’s performance in image classification,image mining,and CBIR.The novelty of the proposed EffNet-CNN model includes the integration of different techniques and modifications.The model includes the Mahalanobis distance metric for feature matching,which enhances the similarity measurements.The model extends EfficientNet architecture by incorporating additional convolutional layers,batch normalization,dropout,and pooling layers for improved hierarchical feature extraction.A systematic hyperparameter optimization using SGD,performance evaluation with three datasets,and data normalization for improving feature representations.The EffNet-CNN is assessed utilizing precision,accuracy,F-measure,and recall metrics across MS-COCO,CIFAR-10 and 100 datasets.The model achieved accuracy values ranging from 90.60%to 95.90%for the MS-COCO dataset,96.8%to 98.3%for the CIFAR-10 dataset and 92.9%to 98.6%for the CIFAR-100 dataset.A validation of the EffNet-CNN model’s results with other models reveals the proposed model’s superior performance.The results highlight the potential of the EffNet-CNN model proposed for image classification and its usefulness in image mining and CBIR.展开更多
Reliable surface height observations over inland water bodies are useful for understanding the hydrological cycle.Satellite radar altimetry particularly contributed with its long-term archive and minimal cloud interfe...Reliable surface height observations over inland water bodies are useful for understanding the hydrological cycle.Satellite radar altimetry particularly contributed with its long-term archive and minimal cloud interference.Specialized inland water altimetry,developed from oceanography and geodesy,is still being extensively investigated.By synthesizing pioneering studies on“retracking algorithms”,this review demonstrates,from a user perspective,why optimizing conventional retracking is still important and how it can extend reliable historical water level retrieval over more ungauged sites.Numerous unrevealed inland water bodies have small sizes or complex surroundings,posing challenges to maintaining accuracy.Applications have shown that a critical key lies in the retracking correction during range retrieval(uncertainty likely on the order of meters),compared with other corrections(on the order of centimeters or decimeters).From multiple uncertainty factors in range retrieval,signal entanglements from land contamination and off-nadir effects are core issues.We evaluate and compared key strategies from prototype retrackers to improved retrackers,especially the empirical ones optimized for inland waters.Sub-waveform extraction and adjustment for Delay-Doppler modes has advanced range retrieval to a new stage.Four innovative inland-water-compatible retrackers are introduced in detail,with a highlight on their distinct approaches to robustly improve performance.Considering the selection of different data and retrackers in varying scenarios,a synthesis analysis is conducted based on results reported in previous literature.In conclusion,the empirical retracking has been enhanced to offer stable decimeter-level accuracy in intricate landscapes(e.g.,small lakes and rivers with varied surroundings).In comparison,the physical retracking has been upgraded to provide greater precision for homogeneous surface in large lakes.For future inland water altimetry,we articulate how additionally retracked results can benefit hydrological applications,and what difficulties would arise when extending study scales.展开更多
Retrieval analysis in total knee arthroplasty(TKA)has been little studied in the literature.A narrative review of the literature to understand the current importance of retrieval analysis in TKA has been conducted.On ...Retrieval analysis in total knee arthroplasty(TKA)has been little studied in the literature.A narrative review of the literature to understand the current importance of retrieval analysis in TKA has been conducted.On August 27,2024,a literature search was performed in PubMed using“TKA retrieval analysis”as keywords.A total of 160 articles were found,of which only 19 were analyzed because they were directly related to the subject of this article.Rotating-platform(mobile-bearing)TKA has no surface damage advantage over fixed-bearing TKA.TKAs with central locking mechanisms are more prone to debond from the cement mantle.No major wear of the polyethylene(PE)component in TKA using oxidized zirconium components occurs.Femoral components of cobalt-chromium roughen more than oxidized zirconium femoral components.The use of a polished tibial tray over an unpolished design is advised.At short-run assessment(15 months on average),antioxidant-stabilized highly crosslinked PE components are not clinically different in surface damage,density of crosslinking,or oxidation compared to standard remelted highly crosslinked PE components.A correlation between implant position and PE component surface damage has been reported.It shows the importance of optimizing component position to reduce PE component damage.Contemporary knee tumor megaendoprostheses show notable volumetric metal wear originated at the rotating hinge.Retrieval analysis in TKA renders relevant data on how different prosthetic designs described in the literature perform.Such information can help to improve future prosthetic designs to increase prosthetic survival.展开更多
To investigate the impact of preoperative serum follicle-stimulating hormone(FSH)levels on the probability of testicular sperm retrieval,we conducted a study of nonobstructive azoospermic(NOA)men with different testic...To investigate the impact of preoperative serum follicle-stimulating hormone(FSH)levels on the probability of testicular sperm retrieval,we conducted a study of nonobstructive azoospermic(NOA)men with different testicular volumes(TVs)who underwent microdissection testicular sperm extraction(micro-TESE).A total of 177 NOA patients undergoing micro-TESE for the first time from April 2019 to November 2022 in Shenzhen Zhongshan Obstetrics and Gynecology Hospital(formerly Shenzhen Zhongshan Urology Hospital,Shenzhen,China)were retrospectively reviewed.The subjects were divided into four groups based on average TV quartiles.Serum hormone levels in each TV group were compared between positive and negative sperm retrieval subgroups.Overall sperm retrieval rate was 57.6%.FSH levels(median[interquartile range])were higher in the positive sperm retrieval subgroup compared with the negative outcome subgroup when average TV was<5 ml(first quartile[Q1:TV<3 ml]:43.32[17.92]IU l^(−1) vs 32.95[18.56]IU l−1,P=0.048;second quartile[Q2:3 ml≤TV<5 ml]:31.31[15.37]IU l^(−1) vs 25.59[18.40]IU l^(−1),P=0.042).Elevated serum FSH levels were associated with successful micro-TESE sperm retrieval in NOA men whose average TVs were<5 ml(adjusted odds ratio[OR]:1.06 per unit increase;95%confidence interval[CI]:1.01–1.11;P=0.011).In men with TVs≥5 ml,larger TVs were associated with lower odds of sperm retrieval(adjusted OR:0.84 per 1 ml increase;95%CI:0.71–0.98;P=0.029).In conclusion,elevated serum FSH levels were associated with positive sperm retrieval in micro-TESE in NOA men with TVs<5 ml.In men with TV≥5 ml,increases in average TVs were associated with lower odds of sperm retrieval.展开更多
Mixed-phase clouds(MPCs)involve complex microphysical and dynamical processes of cloud formation and dissipation,which are crucial for numerical weather prediction and cloud-climate feedback.However,satellite remote s...Mixed-phase clouds(MPCs)involve complex microphysical and dynamical processes of cloud formation and dissipation,which are crucial for numerical weather prediction and cloud-climate feedback.However,satellite remote sensing of MPC properties is still challenging,and there is seldom MPC result inferred from passive spectral observations.This study examines the spectral characteristics of MPCs in the shortwave-infrared(SWIR)channels over the wavelength of 0.4–2.5μm,and evaluates the potential of current operational satellite spectroradiometer channels for MPC retrievals.With optical properties of MPCs based on the assumption of uniform mixing of both ice and liquid water particles,the effects of MPC ice optical thickness fraction(IOTF)and effective radius on associated optical properties are analyzed.As expected,results indicate that the MPC optical properties show features for ice and liquid water clouds,and their spectral variations show noticeable differences from those for homogeneous cases.A radiative transfer method is employed to examine the sensitivity of SWIR channels to given MPC cloud water path(CWP)and IOTF.MPCs have unique signal characteristics in the SWIR spectrum.The 0.87-μm channel is most sensitive to CWP.Meanwhile,the 1.61-and 2.13-μm channels are more sensitive to water-dominated MPCs(IOTF approaching 0),and the 2.25-μm channel is sensitive to both water-dominated and ice-dominated MPCs(IOTF approaching 1).Such spectral differences are potentially possible to be used to infer MPC properties based on radiometer observations,which will be investigated in future studies.展开更多
Infertility,defined as the inability to conceive after 1 year of regular unprotected intercourse,impacts 10%–20%of couples globally.Both male and female factors contribute equally to this condition.Azoospermia,partic...Infertility,defined as the inability to conceive after 1 year of regular unprotected intercourse,impacts 10%–20%of couples globally.Both male and female factors contribute equally to this condition.Azoospermia,particularly nonobstructive azoospermia(NOA),which affects 10%–15%of infertile men,represents a significant challenge in male infertility.The advent of assisted reproductive technology(ART),specifically microdissection testicular sperm extraction(micro-TESE)followed by intracytoplasmic sperm injection(ICSI),offers a possibility for men with NOA to father biological children.Recent studies have focused on the predictors of sperm retrieval in NOA patients,such as age,testicular volume,and follicle-stimulating hormone(FSH)level.This review aims to explore the limited data on the anatomical characteristics of NOA patients and provide surgical considerations for micro-TESE,thereby enhancing understanding and improving outcomes for this challenging condition.展开更多
Indoor visual localization relies heavily on image retrieval to ascertain location information.However,the widespread presence and high consistency of floor patterns across different images of-ten lead to the extracti...Indoor visual localization relies heavily on image retrieval to ascertain location information.However,the widespread presence and high consistency of floor patterns across different images of-ten lead to the extraction of numerous repetitive features,thereby reducing the accuracy of image retrieval.This article proposes an indoor visual localization method based on semantic segmentation and adaptive weight fusion to address the issue of ground texture interference with retrieval results.During the positioning process,an indoor semantic segmentation model is established.Semantic segmentation technology is applied to accurately delineate the ground portion of the images.Fea-ture extraction is performed on both the original database and the ground-segmented database.The vector of locally aggregated descriptors(VLAD)algorithm is then used to convert image features into a fixed-length feature representation,which improves the efficiency of image retrieval.Simul-taneously,a method for adaptive weight optimization in similarity calculation is proposed,using a-daptive weights to compute similarity for different regional features,thereby improving the accuracy of image retrieval.The experimental results indicate that this method significantly reduces ground interference and effectively utilizes ground information,thereby improving the accuracy of image retrieval.展开更多
Aerosol optical depth(AOD)and fine particulate matter with a diameter of less than or equal to 2.5μm(PM_(2.5))play crucial roles in air quality,human health,and climate change.However,the complex correlation of AOD–...Aerosol optical depth(AOD)and fine particulate matter with a diameter of less than or equal to 2.5μm(PM_(2.5))play crucial roles in air quality,human health,and climate change.However,the complex correlation of AOD–PM_(2.5)and the limitations of existing algorithms pose a significant challenge in realizing the accurate joint retrieval of these two parameters at the same location.On this point,a multi-task learning(MTL)model,which enables the joint retrieval of PM_(2.5)concentration and AOD,is proposed and applied on the top-of-the-atmosphere reflectance data gathered by the Fengyun-4A Advanced Geosynchronous Radiation Imager(FY-4A AGRI),and compared to that of two single-task learning models—namely,Random Forest(RF)and Deep Neural Network(DNN).Specifically,MTL achieves a coefficient of determination(R^(2))of 0.88 and a root-mean-square error(RMSE)of 0.10 in AOD retrieval.In comparison to RF,the R^(2)increases by 0.04,the RMSE decreases by 0.02,and the percentage of retrieval results falling within the expected error range(Within-EE)rises by 5.55%.The R^(2)and RMSE of PM_(2.5)retrieval by MTL are 0.84 and 13.76μg m~(-3)respectively.Compared with RF,the R^(2)increases by 0.06,the RMSE decreases by 4.55μg m~(-3),and the Within-EE increases by 7.28%.Additionally,compared to DNN,MTL shows an increase of 0.01 in R^(2)and a decrease of 0.02 in RMSE in AOD retrieval,with a corresponding increase of 2.89%in Within-EE.For PM_(2.5)retrieval,MTL exhibits an increase of 0.05 in R^(2),a decrease of 1.76μg m~(-3)in RMSE,and an increase of 6.83%in Within-EE.The evaluation suggests that MTL is able to provide simultaneously improved AOD and PM_(2.5)retrievals,demonstrating a significant advantage in efficiently capturing the spatial distribution of PM_(2.5)concentration and AOD.展开更多
1 The need to refine journal subject classification systems Journal subject classification systems are fundamental to journal evaluation,research assessments and information retrieval.Previous studies(e.g.,Wang&Wa...1 The need to refine journal subject classification systems Journal subject classification systems are fundamental to journal evaluation,research assessments and information retrieval.Previous studies(e.g.,Wang&Waltman,2016)have identified accuracy issues in major classification systems such as the Subject Categories in the Web of Science and ASJC in Scopus.展开更多
基金The authors would like to thank Dr.Liu Shun for his valuable suggestions.This study was supported by the National Natural Science Foundation of China(Grant Nos.40375009 and 40305003).
文摘A method is developed to assess retrievability, namely the retrieval potential for atmospheric temperature profiles, from satellite infrared measurements in clear-sky conditions. This technique is based upon generalized linear inverse theory and empirical orthogonal function analysis. Utilizing the NCEP global temperature reanalysis data in January and July from 1999 to 2003, the retrievabilities obtained with the Atmospheric Infrared Sounder （AIRS） and the High Resolution Infrared Radiation Sounder/3 （HIRS/3） sounding channel data are derived respectively for each standard pressure level on a global scale. As an incidental result of this study, the optimum truncation number in the method of generalized linear inverse is deduced too. The results show that the retrievabilities of temperature obtained with the two datasets are similar in spatial distribution and seasonal change characteristics. As for the vertical distribution, the retrievabilities are low in the upper and lower atmosphere, and high between 400 hPa and 850 hPa. For the geographical distribution, the retrievabilities are low in the low-latitude oceanic regions and in some regions in Antarctica, and relatively high in mid-high latitudes and continental regions. Compared with the HIRS/3 data, the retrievability obtained with the AIRS data can be improved by an amount between 0.15 and 0.40.
基金This work is supported,in part,by the National Natural Science Foundation of China under grant No.61872069in part,by the Fundamental Research Funds for the Central Universities(N171704005)in part,by the Shenyang Science and Technology Plan Projects(18-013-0-01).
文摘With the development of cloud storage,the problem of efficiently checking and proving data integrity needs more consideration.Therefore,much of growing interest has been pursed in the context of the integrity verification of cloud storage.Provable data possession(PDP)and Proofs of retrievablity(POR)are two kinds of important scheme which can guarantee the data integrity in the cloud storage environments.The main difference between them is that POR schemes store a redundant encoding of the client data on the server so as to she has the ability of retrievablity while PDP does not have.Unfortunately,most of POR schemes support only static data.Stefanov et al.proposed a dynamic POR,but their scheme need a large of amount of client storage and has a large audit cost.Cash et al.use Oblivious RAM(ORAM)to construct a fully dynamic POR scheme,but the cost of their scheme is also very heavy.Based on the idea which proposed by Cash,we propose dynamic proofs of retrievability via Partitioning-Based Square Root Oblivious RAM(DPoR-PSR-ORAM).Firstly,the notions used in our scheme are defined.The Partitioning-Based Square Root Oblivious RAM(PSR-ORAM)protocol is also proposed.The DPOR-PSR-ORAM Model which includes the formal definitions,security definitions and model construction methods are described in the paper.Finally,we give the security analysis and efficiency analysis.The analysis results show that our scheme not only has the property of correctness,authenticity,next-read pattern hiding and retrievabiltiy,but also has the high efficiency.
基金supported in part by the US National Science Foundation under grant CNS-1115548 and a grant from Cisco Research
文摘Data security is a significant issue in cloud storage systems. After outsourcing data to cloud servers, clients lose physical control over the data. To guarantee clients that their data is intact on the server side, some mechanism is needed for clients to periodically check the integrity of their data. Proof of retrievability （PoR） is designed to ensure data integrity. However, most prior PoR schemes focus on static data, and existing dynamic PoR is inefficient. In this paper, we propose a new version of dynamic PoR that is based on a B＋ tree and a Merkle hash tree. We propose a novel authenticated data structure, called Cloud Merkle B＋ tree （CMBT）. By combining CMBT with the BES signature, dynamic operations such as insertion, deletion, and modification are supported. Compared with existing PoR schemes, our scheme improves worst-case overhead from O（n） to O（log n）.
基金sponsored by National Natural Science Foundation of China(No.61571049).
文摘Traceability and trustiness are two critical issues in the logistics sector.Blockchain provides a potential way for logistics tracking systems due to its traits of tamper resistance.However,it is non-trivial to apply blockchain on logistics because of firstly,the binding relationship between virtue data and physical location cannot be guaranteed so that frauds may exist.Secondly,it is neither practical to upload complete data on the blockchain due to the limited storage resources nor convincing to trust the digest of the data.This paper proposes a traceable and trustable consortium blockchain for logistics T^(2)L to provide an efficient solution to the mentioned problems.Specifically,the authenticated geocoding data from telecom operators’base stations are adopted to ensure the location credibility of the data before being uploaded to the blockchain for the purpose of reliable traceability of the logistics.Moreover,we propose a scheme based on Zero Knowledge Proof of Retrievability(ZK BLS-PoR)to ensure the trustiness of the data digest and the proofs to the blockchain.Any user in the system can check the data completeness by verifying the proofs instead of downloading and examining the whole data based on the proposed ZK BLS-PoR scheme,which can provide solid theoretical verification.In all,the proposed T^(2)L framework is a traceable and trustable logistics system with a high level of security.
基金supported by the National Natural Science Foundation of China(Nos.12072027,62103052,61603346 and 62103379)the Henan Key Laboratory of General Aviation Technology,China(No.ZHKF-230201)+3 种基金the Funding for the Open Research Project of the Rotor Aerodynamics Key Laboratory,China(No.RAL20200101)the Key Research and Development Program of Henan Province,China(Nos.241111222000 and 241111222900)the Key Science and Technology Program of Henan Province,China(No.232102220067)the Scholarship Funding from the China Scholarship Council(No.202206030079).
文摘In global navigation satellite system denial environment,cross-view geo-localization based on image retrieval presents an exceedingly critical visual localization solution for Unmanned Aerial Vehicle(UAV)systems.The essence of cross-view geo-localization resides in matching images containing the same geographical targets from disparate platforms,such as UAV-view and satellite-view images.However,images of the same geographical targets may suffer from occlusions and geometric distortions due to variations in the capturing platform,view,and timing.The existing methods predominantly extract features by segmenting feature maps,which overlook the holistic semantic distribution and structural information of objects,resulting in loss of image information.To address these challenges,dilated neighborhood attention Transformer is employed as the feature extraction backbone,and Multi-feature representations based on Multi-scale Hierarchical Contextual Aggregation(MMHCA)is proposed.In the proposed MMHCA method,the multiscale hierarchical contextual aggregation method is utilized to extract contextual information from local to global across various granularity levels,establishing feature associations of contextual information with global and local information in the image.Subsequently,the multi-feature representations method is utilized to obtain rich discriminative feature information,bolstering the robustness of model in scenarios characterized by positional shifts,varying distances,and scale ambiguities.Comprehensive experiments conducted on the extensively utilized University-1652 and SUES-200 benchmarks indicate that the MMHCA method surpasses the existing techniques.showing outstanding results in UAV localization and navigation.
文摘Instrument separation is a critical complication during root canal therapy,impacting treatment success and long-term tooth preservation.The etiology of instrument separation is multifactorial,involving the intricate anatomy of the root canal system,instrument-related factors,and instrumentation techniques.Instrument separation can hinder thorough cleaning,shaping,and obturation of the root canal,posing challenges to successful treatment outcomes.Although retrieval of separated instrument is often feasible,it carries risks including perforation,excessive removal of tooth structure and root fractures.Effective management of separated instruments requires a comprehensive understanding of the contributing factors,meticulous preoperative assessment,and precise evaluation of the retrieval difficulty.The application of appropriate retrieval techniques is essential to minimize complications and optimize clinical outcomes.The current manuscript provides a framework for understanding the causes,risk factors,and clinical management principles of instrument separation.By integrating effective strategies,endodontists can enhance decision-making,improve endodontic treatment success and ensure the preservation of natural dentition.
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.
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.
基金The authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University,Kingdom of Saudi Arabia,for funding this work through the Small Research Group Project under Grant Number RGP.1/316/45.
文摘Content-Based Image Retrieval(CBIR)and image mining are becoming more important study fields in computer vision due to their wide range of applications in healthcare,security,and various domains.The image retrieval system mainly relies on the efficiency and accuracy of the classification models.This research addresses the challenge of enhancing the image retrieval system by developing a novel approach,EfficientNet-Convolutional Neural Network(EffNet-CNN).The key objective of this research is to evaluate the proposed EffNet-CNN model’s performance in image classification,image mining,and CBIR.The novelty of the proposed EffNet-CNN model includes the integration of different techniques and modifications.The model includes the Mahalanobis distance metric for feature matching,which enhances the similarity measurements.The model extends EfficientNet architecture by incorporating additional convolutional layers,batch normalization,dropout,and pooling layers for improved hierarchical feature extraction.A systematic hyperparameter optimization using SGD,performance evaluation with three datasets,and data normalization for improving feature representations.The EffNet-CNN is assessed utilizing precision,accuracy,F-measure,and recall metrics across MS-COCO,CIFAR-10 and 100 datasets.The model achieved accuracy values ranging from 90.60%to 95.90%for the MS-COCO dataset,96.8%to 98.3%for the CIFAR-10 dataset and 92.9%to 98.6%for the CIFAR-100 dataset.A validation of the EffNet-CNN model’s results with other models reveals the proposed model’s superior performance.The results highlight the potential of the EffNet-CNN model proposed for image classification and its usefulness in image mining and CBIR.
基金funded by the National Key Research and Development Program of China(2022YFF0711603)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA28020503)+2 种基金the National Natural Science Foundation of China(Grant No.42371399,42301431)Basic Research Program of Jiangsu(Grant No.BK20240112)the Science and Technology Planning Project of NIGLAS(Grant No.2022NIGLAS-CJH04).
文摘Reliable surface height observations over inland water bodies are useful for understanding the hydrological cycle.Satellite radar altimetry particularly contributed with its long-term archive and minimal cloud interference.Specialized inland water altimetry,developed from oceanography and geodesy,is still being extensively investigated.By synthesizing pioneering studies on“retracking algorithms”,this review demonstrates,from a user perspective,why optimizing conventional retracking is still important and how it can extend reliable historical water level retrieval over more ungauged sites.Numerous unrevealed inland water bodies have small sizes or complex surroundings,posing challenges to maintaining accuracy.Applications have shown that a critical key lies in the retracking correction during range retrieval(uncertainty likely on the order of meters),compared with other corrections(on the order of centimeters or decimeters).From multiple uncertainty factors in range retrieval,signal entanglements from land contamination and off-nadir effects are core issues.We evaluate and compared key strategies from prototype retrackers to improved retrackers,especially the empirical ones optimized for inland waters.Sub-waveform extraction and adjustment for Delay-Doppler modes has advanced range retrieval to a new stage.Four innovative inland-water-compatible retrackers are introduced in detail,with a highlight on their distinct approaches to robustly improve performance.Considering the selection of different data and retrackers in varying scenarios,a synthesis analysis is conducted based on results reported in previous literature.In conclusion,the empirical retracking has been enhanced to offer stable decimeter-level accuracy in intricate landscapes(e.g.,small lakes and rivers with varied surroundings).In comparison,the physical retracking has been upgraded to provide greater precision for homogeneous surface in large lakes.For future inland water altimetry,we articulate how additionally retracked results can benefit hydrological applications,and what difficulties would arise when extending study scales.
文摘Retrieval analysis in total knee arthroplasty(TKA)has been little studied in the literature.A narrative review of the literature to understand the current importance of retrieval analysis in TKA has been conducted.On August 27,2024,a literature search was performed in PubMed using“TKA retrieval analysis”as keywords.A total of 160 articles were found,of which only 19 were analyzed because they were directly related to the subject of this article.Rotating-platform(mobile-bearing)TKA has no surface damage advantage over fixed-bearing TKA.TKAs with central locking mechanisms are more prone to debond from the cement mantle.No major wear of the polyethylene(PE)component in TKA using oxidized zirconium components occurs.Femoral components of cobalt-chromium roughen more than oxidized zirconium femoral components.The use of a polished tibial tray over an unpolished design is advised.At short-run assessment(15 months on average),antioxidant-stabilized highly crosslinked PE components are not clinically different in surface damage,density of crosslinking,or oxidation compared to standard remelted highly crosslinked PE components.A correlation between implant position and PE component surface damage has been reported.It shows the importance of optimizing component position to reduce PE component damage.Contemporary knee tumor megaendoprostheses show notable volumetric metal wear originated at the rotating hinge.Retrieval analysis in TKA renders relevant data on how different prosthetic designs described in the literature perform.Such information can help to improve future prosthetic designs to increase prosthetic survival.
基金supported by the Shenzhen Fundamental Research Program(No.JCYJ20210324121807021).
文摘To investigate the impact of preoperative serum follicle-stimulating hormone(FSH)levels on the probability of testicular sperm retrieval,we conducted a study of nonobstructive azoospermic(NOA)men with different testicular volumes(TVs)who underwent microdissection testicular sperm extraction(micro-TESE).A total of 177 NOA patients undergoing micro-TESE for the first time from April 2019 to November 2022 in Shenzhen Zhongshan Obstetrics and Gynecology Hospital(formerly Shenzhen Zhongshan Urology Hospital,Shenzhen,China)were retrospectively reviewed.The subjects were divided into four groups based on average TV quartiles.Serum hormone levels in each TV group were compared between positive and negative sperm retrieval subgroups.Overall sperm retrieval rate was 57.6%.FSH levels(median[interquartile range])were higher in the positive sperm retrieval subgroup compared with the negative outcome subgroup when average TV was<5 ml(first quartile[Q1:TV<3 ml]:43.32[17.92]IU l^(−1) vs 32.95[18.56]IU l−1,P=0.048;second quartile[Q2:3 ml≤TV<5 ml]:31.31[15.37]IU l^(−1) vs 25.59[18.40]IU l^(−1),P=0.042).Elevated serum FSH levels were associated with successful micro-TESE sperm retrieval in NOA men whose average TVs were<5 ml(adjusted odds ratio[OR]:1.06 per unit increase;95%confidence interval[CI]:1.01–1.11;P=0.011).In men with TVs≥5 ml,larger TVs were associated with lower odds of sperm retrieval(adjusted OR:0.84 per 1 ml increase;95%CI:0.71–0.98;P=0.029).In conclusion,elevated serum FSH levels were associated with positive sperm retrieval in micro-TESE in NOA men with TVs<5 ml.In men with TV≥5 ml,increases in average TVs were associated with lower odds of sperm retrieval.
基金supported by the National Natural Science Foundation of China[Grant Nos.42205086 and 42122038]。
文摘Mixed-phase clouds(MPCs)involve complex microphysical and dynamical processes of cloud formation and dissipation,which are crucial for numerical weather prediction and cloud-climate feedback.However,satellite remote sensing of MPC properties is still challenging,and there is seldom MPC result inferred from passive spectral observations.This study examines the spectral characteristics of MPCs in the shortwave-infrared(SWIR)channels over the wavelength of 0.4–2.5μm,and evaluates the potential of current operational satellite spectroradiometer channels for MPC retrievals.With optical properties of MPCs based on the assumption of uniform mixing of both ice and liquid water particles,the effects of MPC ice optical thickness fraction(IOTF)and effective radius on associated optical properties are analyzed.As expected,results indicate that the MPC optical properties show features for ice and liquid water clouds,and their spectral variations show noticeable differences from those for homogeneous cases.A radiative transfer method is employed to examine the sensitivity of SWIR channels to given MPC cloud water path(CWP)and IOTF.MPCs have unique signal characteristics in the SWIR spectrum.The 0.87-μm channel is most sensitive to CWP.Meanwhile,the 1.61-and 2.13-μm channels are more sensitive to water-dominated MPCs(IOTF approaching 0),and the 2.25-μm channel is sensitive to both water-dominated and ice-dominated MPCs(IOTF approaching 1).Such spectral differences are potentially possible to be used to infer MPC properties based on radiometer observations,which will be investigated in future studies.
文摘Infertility,defined as the inability to conceive after 1 year of regular unprotected intercourse,impacts 10%–20%of couples globally.Both male and female factors contribute equally to this condition.Azoospermia,particularly nonobstructive azoospermia(NOA),which affects 10%–15%of infertile men,represents a significant challenge in male infertility.The advent of assisted reproductive technology(ART),specifically microdissection testicular sperm extraction(micro-TESE)followed by intracytoplasmic sperm injection(ICSI),offers a possibility for men with NOA to father biological children.Recent studies have focused on the predictors of sperm retrieval in NOA patients,such as age,testicular volume,and follicle-stimulating hormone(FSH)level.This review aims to explore the limited data on the anatomical characteristics of NOA patients and provide surgical considerations for micro-TESE,thereby enhancing understanding and improving outcomes for this challenging condition.
基金Supported by the National Natural Science Foundation of China(No.61971162,61771186)the Natural Science Foundation of Heilongjiang Province(No.PL2024F025)+2 种基金the Open Research Fund of National Mobile Communications Research Laboratory Southeast University(No.2023D07)the Outstanding Youth Program of Natural Science Foundation of Heilongjiang Province(No.YQ2020F012)the Funda-mental Scientific Research Funds of Heilongjiang Province(No.2022-KYYWF-1050).
文摘Indoor visual localization relies heavily on image retrieval to ascertain location information.However,the widespread presence and high consistency of floor patterns across different images of-ten lead to the extraction of numerous repetitive features,thereby reducing the accuracy of image retrieval.This article proposes an indoor visual localization method based on semantic segmentation and adaptive weight fusion to address the issue of ground texture interference with retrieval results.During the positioning process,an indoor semantic segmentation model is established.Semantic segmentation technology is applied to accurately delineate the ground portion of the images.Fea-ture extraction is performed on both the original database and the ground-segmented database.The vector of locally aggregated descriptors(VLAD)algorithm is then used to convert image features into a fixed-length feature representation,which improves the efficiency of image retrieval.Simul-taneously,a method for adaptive weight optimization in similarity calculation is proposed,using a-daptive weights to compute similarity for different regional features,thereby improving the accuracy of image retrieval.The experimental results indicate that this method significantly reduces ground interference and effectively utilizes ground information,thereby improving the accuracy of image retrieval.
基金supported by the National Natural Science Foundation of China(Grant Nos.42030708,42375138,42030608,42105128,42075079)the Opening Foundation of Key Laboratory of Atmospheric Sounding,China Meteorological Administration(CMA),and the CMA Research Center on Meteorological Observation Engineering Technology(Grant No.U2021Z03),and the Opening Foundation of the Key Laboratory of Atmospheric Chemistry,CMA(Grant No.2022B02)。
文摘Aerosol optical depth(AOD)and fine particulate matter with a diameter of less than or equal to 2.5μm(PM_(2.5))play crucial roles in air quality,human health,and climate change.However,the complex correlation of AOD–PM_(2.5)and the limitations of existing algorithms pose a significant challenge in realizing the accurate joint retrieval of these two parameters at the same location.On this point,a multi-task learning(MTL)model,which enables the joint retrieval of PM_(2.5)concentration and AOD,is proposed and applied on the top-of-the-atmosphere reflectance data gathered by the Fengyun-4A Advanced Geosynchronous Radiation Imager(FY-4A AGRI),and compared to that of two single-task learning models—namely,Random Forest(RF)and Deep Neural Network(DNN).Specifically,MTL achieves a coefficient of determination(R^(2))of 0.88 and a root-mean-square error(RMSE)of 0.10 in AOD retrieval.In comparison to RF,the R^(2)increases by 0.04,the RMSE decreases by 0.02,and the percentage of retrieval results falling within the expected error range(Within-EE)rises by 5.55%.The R^(2)and RMSE of PM_(2.5)retrieval by MTL are 0.84 and 13.76μg m~(-3)respectively.Compared with RF,the R^(2)increases by 0.06,the RMSE decreases by 4.55μg m~(-3),and the Within-EE increases by 7.28%.Additionally,compared to DNN,MTL shows an increase of 0.01 in R^(2)and a decrease of 0.02 in RMSE in AOD retrieval,with a corresponding increase of 2.89%in Within-EE.For PM_(2.5)retrieval,MTL exhibits an increase of 0.05 in R^(2),a decrease of 1.76μg m~(-3)in RMSE,and an increase of 6.83%in Within-EE.The evaluation suggests that MTL is able to provide simultaneously improved AOD and PM_(2.5)retrievals,demonstrating a significant advantage in efficiently capturing the spatial distribution of PM_(2.5)concentration and AOD.
文摘1 The need to refine journal subject classification systems Journal subject classification systems are fundamental to journal evaluation,research assessments and information retrieval.Previous studies(e.g.,Wang&Waltman,2016)have identified accuracy issues in major classification systems such as the Subject Categories in the Web of Science and ASJC in Scopus.
