Diabetes is a widespread disease affecting millions of people,making it one of the leading causes of death in the world.It is a leading cause of cardiovascular disease and end-stage renal disease.Despite advancements ...Diabetes is a widespread disease affecting millions of people,making it one of the leading causes of death in the world.It is a leading cause of cardiovascular disease and end-stage renal disease.Despite advancements in treatment,including insulin therapy and glucose monitoring devices,diabetes continues to significantly impact quality of life and current modalities do not reverse the end-organ damage associated with its progression.While traditionally indicated for type 1 diabetes,recent clinical practice refinements have made pancreas transplants available to select type 2 diabetics meeting specific criteria.These transplants are usually a part of a simultaneous kidney-pancreas transplant.However,although less frequently performed,transplants of pancreas alone or pancreas after kidney transplant are still available.For selected diabetic patients,pancreas transplants offer significant survival benefits and the improvement of cardiovascular and metabolic complications;however,they are not without risks.Complications such as bleeding,vascular thrombosis,infection,organ leak,and rejection are possible.Another challenge to pancreas transplantation is the decreasing number of procedures being performed due to decline in the volume of available highquality allografts and resource constraints of transplant centers.Advancements in monitoring and treatment of diabetes are contributing to the decline in pancreas transplants nowadays.展开更多
Existing papers on human capital and growth in China has been using single equation estimations.This might cause a simultaneity bias if a two-way causality between the two variables exists.In this paper,the author per...Existing papers on human capital and growth in China has been using single equation estimations.This might cause a simultaneity bias if a two-way causality between the two variables exists.In this paper,the author performs vector autoregressive estimations using panel data on the number of graduates at each level of education as a proxy for human capital in China during 1991-2005.The results show that investment in human capital increases output per worker at all three levels of education.Regarding the effects of output per worker on the accumulation of human capital,the author finds mixed results with the primary-school graduates'benefits the most from increases in per capita output.展开更多
As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods ge...As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods generally have problems such as insufficient 3D scene description capability and low dynamic update efficiency,which are difficult to meet the demand of real-time accurate management.For this reason,this paper proposes a vehicle twin modeling method for road tunnels.This approach starts from the actual management needs,and supports multi-level dynamic modeling from vehicle type,size to color by constructing a vehicle model library that can be flexibly invoked;at the same time,semantic constraint rules with geometric layout,behavioral attributes,and spatial relationships are designed to ensure that the virtual model matches with the real model with a high degree of similarity;ultimately,the prototype system is constructed and the case region is selected for the case study,and the dynamic vehicle status in the tunnel is realized by integrating real-time monitoring data with semantic constraints for precise virtual-real mapping.Finally,the prototype system is constructed and case experiments are conducted in selected case areas,which are combined with real-time monitoring data to realize dynamic updating and three-dimensional visualization of vehicle states in tunnels.The experiments show that the proposed method can run smoothly with an average rendering efficiency of 17.70 ms while guaranteeing the modeling accuracy(composite similarity of 0.867),which significantly improves the real-time and intuitive tunnel management.The research results provide reliable technical support for intelligent operation and emergency response of road tunnels,and offer new ideas for digital twin modeling of complex scenes.展开更多
The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly comple...The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly complex layout combinations.Furthermore,due to constraints in component quantity and geometry within the cross-sectional layout,filler bodies must be incorporated to maintain cross-section performance.Conventional design approaches based on manual experience suffer from inefficiency,high variability,and difficulties in quantification.This paper presents a multi-level automatic filling optimization design method for umbilical cross-sectional layouts to address these limitations.Initially,the research establishes a multi-objective optimization model that considers compactness,balance,and wear resistance of the cross-section,employing an enhanced genetic algorithm to achieve a near-optimal layout.Subsequently,the study implements an image processing-based vacancy detection technique to accurately identify cross-sectional gaps.To manage the variability and diversity of these vacant regions,the research introduces a multi-level filling method that strategically selects and places filler bodies of varying dimensions,overcoming the constraints of uniform-size fillers.Additionally,the method incorporates a hierarchical strategy that subdivides the complex cross-section into multiple layers,enabling layer-by-layer optimization and filling.This approach reduces manufac-turing equipment requirements while ensuring practical production process feasibility.The methodology is validated through a specific umbilical case study.The results demonstrate improvements in compactness,balance,and wear resistance compared with the initial cross-section,offering novel insights and valuable references for filler design in umbilical cross-sections.展开更多
The integration of surface filtration and catalytic decomposition functions in catalytic bags enables the synergistic removal of multiple pollutants(such as dust,nitrogen oxide,acid gases,and dioxins)in a single react...The integration of surface filtration and catalytic decomposition functions in catalytic bags enables the synergistic removal of multiple pollutants(such as dust,nitrogen oxide,acid gases,and dioxins)in a single reactor,thus effectively reducing the cost and operational difficulties associated with flue gas treatment.In this study,Mn-Ce-Sm-Sn(MCSS)catalysts were prepared and loaded onto hightemperature resistant polyimide(P84)filter through ultrasonic impregnation to create composite catalytic filter.The results demonstrate that the NO conversion rates of the composite catalytic filter consistently achieve above 95%within the temperature range of 160-260℃,with a chlorobenzene T_(90)value of 230℃.The ultrasonic impregnation method effectively loaded the catalyst onto the filter,ensuring high dispersion both on the surface and inside the filter.This increased exposure of catalyst active sites enhances the catalytic activity of the composite catalytic filter.Additionally,increasing the catalyst loading leads to a gradual decrease in permeability,an increase in pressure drops and the long residence time of the flue gas,thereby improving catalytic activity.Compared to ordinary impregnation methods,ultrasonic impregnation improves the bonding strength between the catalyst and filter,as well as the permeability of the composite catalytic filter under the same loading conditions.Overall,this study presents a novel approach to prepare composite catalytic filter for the simultaneous removal of NO and chlorobenzene at low temperatures.展开更多
The accuracy of thermal analysis measurements is critical to analyze material properties correctly,making the improvement of measurement precision and proper uncertainty analysis of test results absolutely essential.A...The accuracy of thermal analysis measurements is critical to analyze material properties correctly,making the improvement of measurement precision and proper uncertainty analysis of test results absolutely essential.As a primary thermal analysis instrument,the simultaneous thermal analyzer(STA)has unique advantages,which combines the functionalities of thermogravimetric(TG)analyzersand differential scanning calorimeters(DSC).However,the absence of standard quality control procedures has resulted in poor measurement reproducibility,low accuracy,and inadequate traceability of analytical results.This study utilized a multi-point temperature calibration method based on national certified reference materials to reduce instrument temperature indication errors.On this basis,we innovatively established a comprehensive quality control system encompassing laboratory environmental control,standard method selection,instrument performance verification,reference material traceability,and uncertainty analysis,thereby achieving standardized operational procedures for thermal analysis measurement.Taking the"determination of initial melting temperature of unknown substances"as a representative case study,a component resolution model for thermal analysis test uncertainty was developed.Through systematic analysis of both the reference material-introduced component and measurement repeatability component,complete traceability of test results was achieved.This approach ensures data validity and enhances the accuracy of test results.This provides crucial technical support and practical reference for the standardization of thermal analysis measurement procedure and assessment of result reliability.展开更多
Correction to:Nuclear Science and Techniques(2024)36:8 https://doi.org/10.1007/s41365-024-01570-7 In this article the affiliation details for Author Jian Shan were incorrectly given as‘College of Physics and Electron...Correction to:Nuclear Science and Techniques(2024)36:8 https://doi.org/10.1007/s41365-024-01570-7 In this article the affiliation details for Author Jian Shan were incorrectly given as‘College of Physics and Electronic Engi-neering,Hengyang Normal University,Hengyang 421008,China’but should have been‘School of Nuclear Science and Technology,University of South China,Hengyang 421001,China’.The original article has been corrected.展开更多
Fenton/Fenton-like reactions have gained popularity for their remarkable proficiency in decomposing organic pollutants,especially when enhanced by reductants addition for accel-erating the Fe2+regeneration.Nevertheles...Fenton/Fenton-like reactions have gained popularity for their remarkable proficiency in decomposing organic pollutants,especially when enhanced by reductants addition for accel-erating the Fe2+regeneration.Nevertheless,these works predominantly centered on the formation and utilization of hydroxyl radicals(•OH)in the process,neglecting the evolution of oxidant and reductant due to the difficulty in the simultaneous determination of these two components.By employing the quenching-iodometric method,we could simultaneously determine the concentrations of HSO_(3)-and peroxydisulfate(PDS).This method first employed an excess of peroxymonosulfate(PMS)to effectively quench HSO_(3)-,and then used the iodometric spectrophotometry to simultaneously determine the concentrations of PMS and PDS in the reaction system.Finally,through precise stoichiometric relationships,we could accurately calculate the concentration of HSO_(3)-.Based on this method,we achieved concentration measurements that,upon linear fitting,yielded a correlation coefficient(R^(2))surpassing 0.99,unequivocally affirming the method’s accuracy and trustworthiness.In this work,an innovation approach for determining the concentrations of HSO_(3)-(reductant)and PDS(oxidant)was explored.Additionally,the resilience of the method was verified across different pH levels and in the presence of diverse impurity ions.The results ensured precise concentration measure-ments in the real wastewater.This method was characterized by its simplicity,rapid analysis,and environmental friendliness,offering a newanalytical strategy for the determination of PDS and HSO_(3)-in environmental samples.The method enables more meticulous monitoring of chemical usage in water treatment,facilitating optimized dosing strategies and assessments of reductant-enhanced Fenton or Fenton-like system in water purification.展开更多
Fibers with deformation-triggered responses are essential for smart textiles and wearable electronics.Here,smart core-shell elastomer fibers with a conductive core and a liquid crystal elastomer shell showing simultan...Fibers with deformation-triggered responses are essential for smart textiles and wearable electronics.Here,smart core-shell elastomer fibers with a conductive core and a liquid crystal elastomer shell showing simultaneous resistance and color responses are designed and prepared.The conductive core is consisted of interconnected liquid metal nanodroplets dispersed in a polymer matrix and the elastomer shell is made of cholesteric liquid crystals.When stretched,the fiber resistance increases as the interconnected pathways of liquid metal nanodroplets along the fiber axis become narrower,and the selective reflection color from the fiber surface blueshifts since the cholesteric pitch decreases.The smart elastomer fibers could be woven into smart textiles and respond to various mechanical deformations,including stretching,bending,compression and twisting.The average resistance change is 51%under 100%strain and its variation is smaller than 4%over 500 cycles,showing remarkable fatigue resistance.The simultaneous resistance and color responses to mechanical deformations make the fibers attractive for broad applications,such as flexible electronics.展开更多
Arsenic and cadmium contamination frequently coexist in the real environment.However it remains a challenge for their simultaneous removal due to their distinct physicochemica properties at low cost.To this end,a cost...Arsenic and cadmium contamination frequently coexist in the real environment.However it remains a challenge for their simultaneous removal due to their distinct physicochemica properties at low cost.To this end,a cost-effective magnetic biochar adsorbent (ITBNa800was prepared using biomass waste and iron tailings slag.This composite adsorbent exhibits excellent performance in the simultaneous removal of aqueous As(Ⅴ) and Cd(Ⅱ) even at high concentrations with removal efficiencies of up to 99.98%and 96.04%,respectively.Electro static action,precipitation,and complexation were adsorption mechanisms.As(Ⅴ) and Cd(Ⅱ were synergistic and competitive adsorption.As(Ⅴ) removal was mainly due to physical and chemical adsorption,and 42.40%-58.59%of As(Ⅴ) had been converted to As(Ⅲ ).Cd(Ⅱ) re moval was mainly due to chemical adsorption.Iron oxide and aluminum oxide in ITBNa800were the keys to As(Ⅴ),As(Ⅲ ),and Cd(Ⅱ) adsorption.DFT calculations revealed iron oxide complex As(Ⅴ),As(Ⅲ ),and Cd(Ⅱ) molecular clusters through bidentate binuclear,bidentate binuclear,and monodentate binuclear pathways,respectively.Aluminum oxide complex Cd(Ⅱ) molecular cluster through a bidentate mononuclear pathway.We hope the ITBNa800adsorbent and its involved mechanism could offer inspiration in the simultaneous treat ment of As and Cd pollution.展开更多
The“First Multidisciplinary Forum on COVID-19,”as one of the pivotal medical forums organized by China during the initial outbreak of the pandemic,garnered significant attention from numerous countries worldwide.Ens...The“First Multidisciplinary Forum on COVID-19,”as one of the pivotal medical forums organized by China during the initial outbreak of the pandemic,garnered significant attention from numerous countries worldwide.Ensuring the seamless execution of the forum’s translation necessitated exceptionally high standards for simultaneous interpreters.This paper,through the lens of the Translation as Adaptation and Selection theory within Eco-Translatology,conducts an analytical study of the live simultaneous interpretation at the First Multidisciplinary Forum on COVID-19.It examines the interpreters’adaptations and selections across multiple dimensions-namely,linguistic,cultural,and communicative-with the aim of elucidating the guiding role and recommendations that Eco-Translatology can offer to simultaneous interpretation.Furthermore,it seeks to provide insights that may enhance the quality of interpreters’oral translations.展开更多
Accurate prediction of landslide displacement is crucial for effective early warning of landslide disasters.While most existing prediction methods focus on time-series forecasting for individual monitoring points,ther...Accurate prediction of landslide displacement is crucial for effective early warning of landslide disasters.While most existing prediction methods focus on time-series forecasting for individual monitoring points,there is limited research on the spatiotemporal characteristics of landslide deformation.This paper proposes a novel Multi-Relation Spatiotemporal Graph Residual Network with Multi-Level Feature Attention(MFA-MRSTGRN)that effectively improves the prediction performance of landslide displacement through spatiotemporal fusion.This model integrates internal seepage factors as data feature enhancements with external triggering factors,allowing for accurate capture of the complex spatiotemporal characteristics of landslide displacement and the construction of a multi-source heterogeneous dataset.The MFA-MRSTGRN model incorporates dynamic graph theory and four key modules:multilevel feature attention,temporal-residual decomposition,spatial multi-relational graph convolution,and spatiotemporal fusion prediction.This comprehensive approach enables the efficient analyses of multi-source heterogeneous datasets,facilitating adaptive exploration of the evolving multi-relational,multi-dimensional spatiotemporal complexities in landslides.When applying this model to predict the displacement of the Liangshuijing landslide,we demonstrate that the MFA-MRSTGRN model surpasses traditional models,such as random forest(RF),long short-term memory(LSTM),and spatial temporal graph convolutional networks(ST-GCN)models in terms of various evaluation metrics including mean absolute error(MAE=1.27 mm),root mean square error(RMSE=1.49 mm),mean absolute percentage error(MAPE=0.026),and R-squared(R^(2)=0.88).Furthermore,feature ablation experiments indicate that incorporating internal seepage factors improves the predictive performance of landslide displacement models.This research provides an advanced and reliable method for landslide displacement prediction.展开更多
BACKGROUND Alveolar and cystic echinococcoses are lethal zoonotic diseases caused by Echinococcus multilocularis and Echinococcus granulosus infections,leading to alveolar echinococcosis(AE)or cystic echinococcosis(CE...BACKGROUND Alveolar and cystic echinococcoses are lethal zoonotic diseases caused by Echinococcus multilocularis and Echinococcus granulosus infections,leading to alveolar echinococcosis(AE)or cystic echinococcosis(CE),respectively.No study has hitherto reported effective treatment approaches for AE or CE with concurrent hepatorenal involvement.AIM To investigate the feasibility and efficacy of simultaneous combined surgery(SCS)as a comprehensive treatment approach for patients with hepatorenal echinococcosis.METHODS Clinical datasets of hepatorenal AE(n=10)and CE(n=11)patients were retrospectively collected and systematically analyzed.The SCS approach was introduced,and surgical outcomes,complications,and prognoses were documented in detail.RESULTS The SCS approach incorporated hybridized techniques,including partial hepatectomy,partial or total nephrectomy,ex vivo liver resection and autotransplantation,and total or subtotal cystectomy with endocystectomy.Radical SCS was achieved in 100%of AE patients and 63.6%of CE patients.All surgeries were completed without intraoperative complications.The short-term complication rate was 28.6%(Clavien-Dindo classification:AE-1 IIIb,3 IIIa;CE-2 II),while the long-term complication rate was 4.8%(Clavien-Dindo classification:AE-1 IIIb).Patients were followed up for a median of 37 months(AE:6-81 months;CE:34-123 months),with no reported deaths or disease relapses.CONCLUSION CS appears to be a feasible and effective treatment method for patients with hepatorenal involvement of AE or CE.It fulfills the management criteria for advanced AE or CE cases,aiming to maximize patient benefits.展开更多
Heterotrophic denitrification based on polylactic acid(PLAHD)can remove nitrate effectively,but it is expensive and can't remove phosphate.Autotrophic denitrification based on iron sulfide(ISAD)can simultaneously ...Heterotrophic denitrification based on polylactic acid(PLAHD)can remove nitrate effectively,but it is expensive and can't remove phosphate.Autotrophic denitrification based on iron sulfide(ISAD)can simultaneously remove nitrate and phosphate cost-effectively,but its nitrate rate is slow.So,iron sulfide mineral/polylactic acid mixotrophic biofilter(ISPLAB)was constructed to combine advantages of ISAD and PLAHD.ISPLAB achieved nitrogen and phosphorus removal rates of 98.04%and 94.12%,respectively,at a hydraulic retention time(HRT)of 24 h.The study also revealed that controlling molecular weight(MW)of PLA improved the release of soluble organic matter;adding iron sulfide enhanced the hydrolysis of PLA and precipitated PO_(4)^(3-) of Fe^(2+)/Fe^(3+),thereby facilitated simultaneous nitrogen and phosphorus removal.Microbial community analysis resulted that denitrifying bacterias(Phaeodactylibacter and Methylotenera),sulfur-reducing bacterias(Hyphomicrobium),sulfur-oxidizing bacteria(Denitratisoma),iron-reducing bacteria(Romboutsia)and hydrolyzed bacterias(norank_f_norank_o_1-20 and norank_f_Caldilineaceae)coexisted in the ISPLAB system.Organics and iron sulfide drived the denitrification process in ISPLAB.展开更多
As we look ahead to future lunar exploration missions, such as crewed lunar exploration and establishing lunar scientific research stations, the lunar rovers will need to cover vast distances. These distances could ra...As we look ahead to future lunar exploration missions, such as crewed lunar exploration and establishing lunar scientific research stations, the lunar rovers will need to cover vast distances. These distances could range from kilometers to tens of kilometers, and even hundreds and thousands of kilometers. Therefore, it is crucial to develop effective long-range path planning for lunar rovers to meet the demands of lunar patrol exploration. This paper presents a hierarchical map model path planning method that utilizes the existing high-resolution images, digital elevation models and mineral abundance maps. The objective is to address the issue of the construction of lunar rover travel costs in the absence of large-scale, high-resolution digital elevation models. This method models the reference and semantic layers using the middle- and low-resolution remote sensing data. The multi-scale obstacles on the lunar surface are extracted by combining the deep learning algorithm on the high-resolution image, and the obstacle avoidance layer is modeled. A two-stage exploratory path planning decision is employed for long-distance driving path planning on a global–local scale. The proposed method analyzes the long-distance accessibility of various areas of scientific significance, such as Rima Bode. A high-precision digital elevation model is created using stereo images to validate the method. Based on the findings, it can be observed that the entire route spans a distance of 930.32 km. The route demonstrates an impressive ability to avoid meter-level impact craters and linear structures while maintaining an average slope of less than 8°. This paper explores scientific research by traversing at least seven basalt units, uncovering the secrets of lunar volcanic activities, and establishing ‘golden spike’ reference points for lunar stratigraphy. The final result of path planning can serve as a valuable reference for the design, mission demonstration, and subsequent project implementation of the new manned lunar rover.展开更多
Deep learning networks are increasingly exploited in the field of neuronal soma segmentation.However,annotating dataset is also an expensive and time-consuming task.Unsupervised domain adaptation is an effective metho...Deep learning networks are increasingly exploited in the field of neuronal soma segmentation.However,annotating dataset is also an expensive and time-consuming task.Unsupervised domain adaptation is an effective method to mitigate the problem,which is able to learn an adaptive segmentation model by transferring knowledge from a rich-labeled source domain.In this paper,we propose a multi-level distribution alignment-based unsupervised domain adaptation network(MDA-Net)for segmentation of 3D neuronal soma images.Distribution alignment is performed in both feature space and output space.In the feature space,features from different scales are adaptively fused to enhance the feature extraction capability for small target somata and con-strained to be domain invariant by adversarial adaptation strategy.In the output space,local discrepancy maps that can reveal the spatial structures of somata are constructed on the predicted segmentation results.Then thedistribution alignment is performed on the local discrepancies maps across domains to obtain a superior discrepancy map in the target domain,achieving refined segmentation performance of neuronal somata.Additionally,after a period of distribution align-ment procedure,a portion of target samples with high confident pseudo-labels are selected as training data,which assist in learning a more adaptive segmentation network.We verified the superiority of the proposed algorithm by comparing several domain adaptation networks on two 3D mouse brain neuronal somata datasets and one macaque brain neuronal soma dataset.展开更多
Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to vari...Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to various factors,including scattering noise,low contrast,and limited resolution in ultrasound images.Although existing segmentation models have made progress,they still suffer from several limitations,such as high error rates,low generalizability,overfitting,limited feature learning capability,etc.To address these challenges,this paper proposes a Multi-level Relation Transformer-based U-Net(MLRT-UNet)to improve thyroid nodule segmentation.The MLRTUNet leverages a novel Relation Transformer,which processes images at multiple scales,overcoming the limitations of traditional encoding methods.This transformer integrates both local and global features effectively through selfattention and cross-attention units,capturing intricate relationships within the data.The approach also introduces a Co-operative Transformer Fusion(CTF)module to combine multi-scale features from different encoding layers,enhancing the model’s ability to capture complex patterns in the data.Furthermore,the Relation Transformer block enhances long-distance dependencies during the decoding process,improving segmentation accuracy.Experimental results showthat the MLRT-UNet achieves high segmentation accuracy,reaching 98.2% on the Digital Database Thyroid Image(DDT)dataset,97.8% on the Thyroid Nodule 3493(TG3K)dataset,and 98.2% on the Thyroid Nodule3K(TN3K)dataset.These findings demonstrate that the proposed method significantly enhances the accuracy of thyroid nodule segmentation,addressing the limitations of existing models.展开更多
DNA repair enzymes are important in the repair of DNA lesions for maintaining the genome stability,and their abnormal expression induced various human cancers.Simultaneous detection of these DNA enzymes could provide ...DNA repair enzymes are important in the repair of DNA lesions for maintaining the genome stability,and their abnormal expression induced various human cancers.Simultaneous detection of these DNA enzymes could provide convincing evidence based on the comparison of the activity of multiple enzymes than on that of single enzyme.Although fluorescence approach has been applied for the simultaneous detection both of DNA repair enzymes,the spectral overlap and multiwavelength excitation severely restrict the number of available fluorophores.Thus,it is difficult to simultaneously detect three enzymes in a single analysis by fluorescence detection.Herein,we developed a method for the simultaneous determination of three DNA repair enzymes including human flap DNA endonuclease 1(FEN1),human alkyladenine DNA glycosylase(hAAG)and uracil DNA glycosylase(UDG)based on the combination of template-free amplification system with capillary electrophoresis-laser induced fluorescence(CE-LIF)detection.The amplification system was adopted to transfer and amplify the enzymatic products into different length DNA fragments which could be separated effectively by CE-LIF without the complicated modification of the capillary inner wall or labeling different tails on signal probes for separation.The method demonstrated a detection limit of 0.07 U/mL(0.08-160 U/mL)for FEN1,2.40 U/mL(2.5-250U/mL)for hAAG and 2.1×10^(-4)U/mL(0.0004-2.5 U/mL)for UDG,the relative standard deviations(RSDs)of peak time and peak area for different analytes were as follows:2.50%-4,37%and 3.24%-7.18%(inter-day);1.37%-2.71%and 1.43%-3.02%(intra-day),4.28%-6.08%and 4.16%-7.57%(column to column),respectively.And it can identify the inhibitor-like drugs,evaluate enzymatic kinetics and achieve the detection of three enzymes in cell extracts,providing a simple and powerful platform for simultaneous detection of more DNA repair enzymes.展开更多
Blended acquisition offers efficiency improvements over conventional seismic data acquisition, at the cost of introducing blending noise effects. Besides, seismic data often suffers from irregularly missing shots caus...Blended acquisition offers efficiency improvements over conventional seismic data acquisition, at the cost of introducing blending noise effects. Besides, seismic data often suffers from irregularly missing shots caused by artificial or natural effects during blended acquisition. Therefore, blending noise attenuation and missing shots reconstruction are essential for providing high-quality seismic data for further seismic processing and interpretation. The iterative shrinkage thresholding algorithm can help obtain deblended data based on sparsity assumptions of complete unblended data, and it characterizes seismic data linearly. Supervised learning algorithms can effectively capture the nonlinear relationship between incomplete pseudo-deblended data and complete unblended data. However, the dependence on complete unblended labels limits their practicality in field applications. Consequently, a self-supervised algorithm is presented for simultaneous deblending and interpolation of incomplete blended data, which minimizes the difference between simulated and observed incomplete pseudo-deblended data. The used blind-trace U-Net (BTU-Net) prevents identity mapping during complete unblended data estimation. Furthermore, a multistep process with blending noise simulation-subtraction and missing traces reconstruction-insertion is used in each step to improve the deblending and interpolation performance. Experiments with synthetic and field incomplete blended data demonstrate the effectiveness of the multistep self-supervised BTU-Net algorithm.展开更多
This paper addresses the Multi-Vehicle Routing Problem with Time Windows and Simultaneous Pickup and Delivery(MVRPTWSPD),aiming to optimize logistics distribution routes and minimize total costs.A vehicle routing opti...This paper addresses the Multi-Vehicle Routing Problem with Time Windows and Simultaneous Pickup and Delivery(MVRPTWSPD),aiming to optimize logistics distribution routes and minimize total costs.A vehicle routing optimization model is developed based on the operational requirements of the KS Logistics Center,focusing on minimizing vehicle dispatch,loading and unloading,operating,and time window penalty costs.The model incorporates constraints such as vehicle capacity,time windows,and travel distance,and is solved using a genetic algorithm to ensure optimal route planning.Through MATLAB simulations,34 customer points are analyzed,demonstrating that the simultaneous pickup and delivery model reduces total costs by 30.13%,increases vehicle loading rates by 20.04%,and decreases travel distance compared to delivery-only or pickup-only models.The results demonstrate the significant advantages of the simultaneous pickup and delivery mode in reducing logistics costs and improving vehicle utilization,offering valuable insights for enhancing the operational efficiency of the KS Logistics Center.展开更多
文摘Diabetes is a widespread disease affecting millions of people,making it one of the leading causes of death in the world.It is a leading cause of cardiovascular disease and end-stage renal disease.Despite advancements in treatment,including insulin therapy and glucose monitoring devices,diabetes continues to significantly impact quality of life and current modalities do not reverse the end-organ damage associated with its progression.While traditionally indicated for type 1 diabetes,recent clinical practice refinements have made pancreas transplants available to select type 2 diabetics meeting specific criteria.These transplants are usually a part of a simultaneous kidney-pancreas transplant.However,although less frequently performed,transplants of pancreas alone or pancreas after kidney transplant are still available.For selected diabetic patients,pancreas transplants offer significant survival benefits and the improvement of cardiovascular and metabolic complications;however,they are not without risks.Complications such as bleeding,vascular thrombosis,infection,organ leak,and rejection are possible.Another challenge to pancreas transplantation is the decreasing number of procedures being performed due to decline in the volume of available highquality allografts and resource constraints of transplant centers.Advancements in monitoring and treatment of diabetes are contributing to the decline in pancreas transplants nowadays.
文摘Existing papers on human capital and growth in China has been using single equation estimations.This might cause a simultaneity bias if a two-way causality between the two variables exists.In this paper,the author performs vector autoregressive estimations using panel data on the number of graduates at each level of education as a proxy for human capital in China during 1991-2005.The results show that investment in human capital increases output per worker at all three levels of education.Regarding the effects of output per worker on the accumulation of human capital,the author finds mixed results with the primary-school graduates'benefits the most from increases in per capita output.
基金National Natural Science Foundation of China(Nos.42301473,42271424,42171397)Chinese Postdoctoral Innovation Talents Support Program(No.BX20230299)+2 种基金China Postdoctoral Science Foundation(No.2023M742884)Natural Science Foundation of Sichuan Province(Nos.24NSFSC2264,2025ZNSFSC0322)Key Research and Development Project of Sichuan Province(No.24ZDYF0633).
文摘As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods generally have problems such as insufficient 3D scene description capability and low dynamic update efficiency,which are difficult to meet the demand of real-time accurate management.For this reason,this paper proposes a vehicle twin modeling method for road tunnels.This approach starts from the actual management needs,and supports multi-level dynamic modeling from vehicle type,size to color by constructing a vehicle model library that can be flexibly invoked;at the same time,semantic constraint rules with geometric layout,behavioral attributes,and spatial relationships are designed to ensure that the virtual model matches with the real model with a high degree of similarity;ultimately,the prototype system is constructed and the case region is selected for the case study,and the dynamic vehicle status in the tunnel is realized by integrating real-time monitoring data with semantic constraints for precise virtual-real mapping.Finally,the prototype system is constructed and case experiments are conducted in selected case areas,which are combined with real-time monitoring data to realize dynamic updating and three-dimensional visualization of vehicle states in tunnels.The experiments show that the proposed method can run smoothly with an average rendering efficiency of 17.70 ms while guaranteeing the modeling accuracy(composite similarity of 0.867),which significantly improves the real-time and intuitive tunnel management.The research results provide reliable technical support for intelligent operation and emergency response of road tunnels,and offer new ideas for digital twin modeling of complex scenes.
基金financially supported by Guangdong Province Basic and Applied Basic Research Fund Project(Grant No.2022B1515250009)Liaoning Provincial Natural Science Foundation-Doctoral Research Start-up Fund Project(Grant No.2024-BSBA-05)+1 种基金Major Science and Technology Innovation Project in Shandong Province(Grant No.2024CXGC010803)the National Natural Science Foundation of China(Grant Nos.52271269 and 12302147).
文摘The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly complex layout combinations.Furthermore,due to constraints in component quantity and geometry within the cross-sectional layout,filler bodies must be incorporated to maintain cross-section performance.Conventional design approaches based on manual experience suffer from inefficiency,high variability,and difficulties in quantification.This paper presents a multi-level automatic filling optimization design method for umbilical cross-sectional layouts to address these limitations.Initially,the research establishes a multi-objective optimization model that considers compactness,balance,and wear resistance of the cross-section,employing an enhanced genetic algorithm to achieve a near-optimal layout.Subsequently,the study implements an image processing-based vacancy detection technique to accurately identify cross-sectional gaps.To manage the variability and diversity of these vacant regions,the research introduces a multi-level filling method that strategically selects and places filler bodies of varying dimensions,overcoming the constraints of uniform-size fillers.Additionally,the method incorporates a hierarchical strategy that subdivides the complex cross-section into multiple layers,enabling layer-by-layer optimization and filling.This approach reduces manufac-turing equipment requirements while ensuring practical production process feasibility.The methodology is validated through a specific umbilical case study.The results demonstrate improvements in compactness,balance,and wear resistance compared with the initial cross-section,offering novel insights and valuable references for filler design in umbilical cross-sections.
基金Project supported by the National Key Research and Development Program of China(2021YFB3500600,2021YFB3500605)Natural Science Foundation of Jiangsu Province(BK20220365)+5 种基金Key R&D Program of Jiangsu Province(BE2022142)Natural Science Foundation of the Jiangsu Higher Education Institutions of China(22KJB610002)Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX23_1419)Science and Technology Plan of Yangzhou(YZ2022030,YZ2023020)the State Key Laboratory of Clean and Efficient Coal-fired Power Generation and Pollution Control(D2022FK098)。
文摘The integration of surface filtration and catalytic decomposition functions in catalytic bags enables the synergistic removal of multiple pollutants(such as dust,nitrogen oxide,acid gases,and dioxins)in a single reactor,thus effectively reducing the cost and operational difficulties associated with flue gas treatment.In this study,Mn-Ce-Sm-Sn(MCSS)catalysts were prepared and loaded onto hightemperature resistant polyimide(P84)filter through ultrasonic impregnation to create composite catalytic filter.The results demonstrate that the NO conversion rates of the composite catalytic filter consistently achieve above 95%within the temperature range of 160-260℃,with a chlorobenzene T_(90)value of 230℃.The ultrasonic impregnation method effectively loaded the catalyst onto the filter,ensuring high dispersion both on the surface and inside the filter.This increased exposure of catalyst active sites enhances the catalytic activity of the composite catalytic filter.Additionally,increasing the catalyst loading leads to a gradual decrease in permeability,an increase in pressure drops and the long residence time of the flue gas,thereby improving catalytic activity.Compared to ordinary impregnation methods,ultrasonic impregnation improves the bonding strength between the catalyst and filter,as well as the permeability of the composite catalytic filter under the same loading conditions.Overall,this study presents a novel approach to prepare composite catalytic filter for the simultaneous removal of NO and chlorobenzene at low temperatures.
文摘The accuracy of thermal analysis measurements is critical to analyze material properties correctly,making the improvement of measurement precision and proper uncertainty analysis of test results absolutely essential.As a primary thermal analysis instrument,the simultaneous thermal analyzer(STA)has unique advantages,which combines the functionalities of thermogravimetric(TG)analyzersand differential scanning calorimeters(DSC).However,the absence of standard quality control procedures has resulted in poor measurement reproducibility,low accuracy,and inadequate traceability of analytical results.This study utilized a multi-point temperature calibration method based on national certified reference materials to reduce instrument temperature indication errors.On this basis,we innovatively established a comprehensive quality control system encompassing laboratory environmental control,standard method selection,instrument performance verification,reference material traceability,and uncertainty analysis,thereby achieving standardized operational procedures for thermal analysis measurement.Taking the"determination of initial melting temperature of unknown substances"as a representative case study,a component resolution model for thermal analysis test uncertainty was developed.Through systematic analysis of both the reference material-introduced component and measurement repeatability component,complete traceability of test results was achieved.This approach ensures data validity and enhances the accuracy of test results.This provides crucial technical support and practical reference for the standardization of thermal analysis measurement procedure and assessment of result reliability.
文摘Correction to:Nuclear Science and Techniques(2024)36:8 https://doi.org/10.1007/s41365-024-01570-7 In this article the affiliation details for Author Jian Shan were incorrectly given as‘College of Physics and Electronic Engi-neering,Hengyang Normal University,Hengyang 421008,China’but should have been‘School of Nuclear Science and Technology,University of South China,Hengyang 421001,China’.The original article has been corrected.
基金supported by National Natural Scienc Foundation of China(No.52400097)the Nanqiang Young Talents Supporting Program from Xiamen University.
文摘Fenton/Fenton-like reactions have gained popularity for their remarkable proficiency in decomposing organic pollutants,especially when enhanced by reductants addition for accel-erating the Fe2+regeneration.Nevertheless,these works predominantly centered on the formation and utilization of hydroxyl radicals(•OH)in the process,neglecting the evolution of oxidant and reductant due to the difficulty in the simultaneous determination of these two components.By employing the quenching-iodometric method,we could simultaneously determine the concentrations of HSO_(3)-and peroxydisulfate(PDS).This method first employed an excess of peroxymonosulfate(PMS)to effectively quench HSO_(3)-,and then used the iodometric spectrophotometry to simultaneously determine the concentrations of PMS and PDS in the reaction system.Finally,through precise stoichiometric relationships,we could accurately calculate the concentration of HSO_(3)-.Based on this method,we achieved concentration measurements that,upon linear fitting,yielded a correlation coefficient(R^(2))surpassing 0.99,unequivocally affirming the method’s accuracy and trustworthiness.In this work,an innovation approach for determining the concentrations of HSO_(3)-(reductant)and PDS(oxidant)was explored.Additionally,the resilience of the method was verified across different pH levels and in the presence of diverse impurity ions.The results ensured precise concentration measure-ments in the real wastewater.This method was characterized by its simplicity,rapid analysis,and environmental friendliness,offering a newanalytical strategy for the determination of PDS and HSO_(3)-in environmental samples.The method enables more meticulous monitoring of chemical usage in water treatment,facilitating optimized dosing strategies and assessments of reductant-enhanced Fenton or Fenton-like system in water purification.
基金supported by the National Natural Science Foundation of China(No.22278352)National Key Research and Development Program of China(No.2021YFC3001100)。
文摘Fibers with deformation-triggered responses are essential for smart textiles and wearable electronics.Here,smart core-shell elastomer fibers with a conductive core and a liquid crystal elastomer shell showing simultaneous resistance and color responses are designed and prepared.The conductive core is consisted of interconnected liquid metal nanodroplets dispersed in a polymer matrix and the elastomer shell is made of cholesteric liquid crystals.When stretched,the fiber resistance increases as the interconnected pathways of liquid metal nanodroplets along the fiber axis become narrower,and the selective reflection color from the fiber surface blueshifts since the cholesteric pitch decreases.The smart elastomer fibers could be woven into smart textiles and respond to various mechanical deformations,including stretching,bending,compression and twisting.The average resistance change is 51%under 100%strain and its variation is smaller than 4%over 500 cycles,showing remarkable fatigue resistance.The simultaneous resistance and color responses to mechanical deformations make the fibers attractive for broad applications,such as flexible electronics.
基金supported by the National Natural Science Foundation of China(NSFC)grants(Nos.41473122,41173113,52261145693 and 22106028)the Ministry of Science and Technology of the People’s Republic of China(MOST)+1 种基金the Fundamental Research Funds for the Central Universities(FRF-TP-19-020A1)the Hundred Talents Program of the Chinese Academy of Sciences,and China Postdoctoral Science Foundation(No.2023M730216).
文摘Arsenic and cadmium contamination frequently coexist in the real environment.However it remains a challenge for their simultaneous removal due to their distinct physicochemica properties at low cost.To this end,a cost-effective magnetic biochar adsorbent (ITBNa800was prepared using biomass waste and iron tailings slag.This composite adsorbent exhibits excellent performance in the simultaneous removal of aqueous As(Ⅴ) and Cd(Ⅱ) even at high concentrations with removal efficiencies of up to 99.98%and 96.04%,respectively.Electro static action,precipitation,and complexation were adsorption mechanisms.As(Ⅴ) and Cd(Ⅱ were synergistic and competitive adsorption.As(Ⅴ) removal was mainly due to physical and chemical adsorption,and 42.40%-58.59%of As(Ⅴ) had been converted to As(Ⅲ ).Cd(Ⅱ) re moval was mainly due to chemical adsorption.Iron oxide and aluminum oxide in ITBNa800were the keys to As(Ⅴ),As(Ⅲ ),and Cd(Ⅱ) adsorption.DFT calculations revealed iron oxide complex As(Ⅴ),As(Ⅲ ),and Cd(Ⅱ) molecular clusters through bidentate binuclear,bidentate binuclear,and monodentate binuclear pathways,respectively.Aluminum oxide complex Cd(Ⅱ) molecular cluster through a bidentate mononuclear pathway.We hope the ITBNa800adsorbent and its involved mechanism could offer inspiration in the simultaneous treat ment of As and Cd pollution.
文摘The“First Multidisciplinary Forum on COVID-19,”as one of the pivotal medical forums organized by China during the initial outbreak of the pandemic,garnered significant attention from numerous countries worldwide.Ensuring the seamless execution of the forum’s translation necessitated exceptionally high standards for simultaneous interpreters.This paper,through the lens of the Translation as Adaptation and Selection theory within Eco-Translatology,conducts an analytical study of the live simultaneous interpretation at the First Multidisciplinary Forum on COVID-19.It examines the interpreters’adaptations and selections across multiple dimensions-namely,linguistic,cultural,and communicative-with the aim of elucidating the guiding role and recommendations that Eco-Translatology can offer to simultaneous interpretation.Furthermore,it seeks to provide insights that may enhance the quality of interpreters’oral translations.
基金the funding support from the National Natural Science Foundation of China(Grant No.52308340)Chongqing Talent Innovation and Entrepreneurship Demonstration Team Project(Grant No.cstc2024ycjh-bgzxm0012)the Science and Technology Projects supported by China Coal Technology and Engineering Chongqing Design and Research Institute(Group)Co.,Ltd.(Grant No.H20230317).
文摘Accurate prediction of landslide displacement is crucial for effective early warning of landslide disasters.While most existing prediction methods focus on time-series forecasting for individual monitoring points,there is limited research on the spatiotemporal characteristics of landslide deformation.This paper proposes a novel Multi-Relation Spatiotemporal Graph Residual Network with Multi-Level Feature Attention(MFA-MRSTGRN)that effectively improves the prediction performance of landslide displacement through spatiotemporal fusion.This model integrates internal seepage factors as data feature enhancements with external triggering factors,allowing for accurate capture of the complex spatiotemporal characteristics of landslide displacement and the construction of a multi-source heterogeneous dataset.The MFA-MRSTGRN model incorporates dynamic graph theory and four key modules:multilevel feature attention,temporal-residual decomposition,spatial multi-relational graph convolution,and spatiotemporal fusion prediction.This comprehensive approach enables the efficient analyses of multi-source heterogeneous datasets,facilitating adaptive exploration of the evolving multi-relational,multi-dimensional spatiotemporal complexities in landslides.When applying this model to predict the displacement of the Liangshuijing landslide,we demonstrate that the MFA-MRSTGRN model surpasses traditional models,such as random forest(RF),long short-term memory(LSTM),and spatial temporal graph convolutional networks(ST-GCN)models in terms of various evaluation metrics including mean absolute error(MAE=1.27 mm),root mean square error(RMSE=1.49 mm),mean absolute percentage error(MAPE=0.026),and R-squared(R^(2)=0.88).Furthermore,feature ablation experiments indicate that incorporating internal seepage factors improves the predictive performance of landslide displacement models.This research provides an advanced and reliable method for landslide displacement prediction.
基金Supported by the National Natural Science Foundation of China,No.82360111Xinjiang Science and Technology Department-Leading Talents in Technological Innovation-High-Level Leading Talents,No.2022TSYCLJ0034+1 种基金State Key Laboratory for The Cause and Control of High Incidence in Central Asia Jointly Constructed by The Ministry and The Province,No.SKL-HIDCA-2023-2 and No.SKLHIDCA-2024-22Xinjiang Uygur Autonomous Region Graduate Innovation Program,No.XJ2024G153.
文摘BACKGROUND Alveolar and cystic echinococcoses are lethal zoonotic diseases caused by Echinococcus multilocularis and Echinococcus granulosus infections,leading to alveolar echinococcosis(AE)or cystic echinococcosis(CE),respectively.No study has hitherto reported effective treatment approaches for AE or CE with concurrent hepatorenal involvement.AIM To investigate the feasibility and efficacy of simultaneous combined surgery(SCS)as a comprehensive treatment approach for patients with hepatorenal echinococcosis.METHODS Clinical datasets of hepatorenal AE(n=10)and CE(n=11)patients were retrospectively collected and systematically analyzed.The SCS approach was introduced,and surgical outcomes,complications,and prognoses were documented in detail.RESULTS The SCS approach incorporated hybridized techniques,including partial hepatectomy,partial or total nephrectomy,ex vivo liver resection and autotransplantation,and total or subtotal cystectomy with endocystectomy.Radical SCS was achieved in 100%of AE patients and 63.6%of CE patients.All surgeries were completed without intraoperative complications.The short-term complication rate was 28.6%(Clavien-Dindo classification:AE-1 IIIb,3 IIIa;CE-2 II),while the long-term complication rate was 4.8%(Clavien-Dindo classification:AE-1 IIIb).Patients were followed up for a median of 37 months(AE:6-81 months;CE:34-123 months),with no reported deaths or disease relapses.CONCLUSION CS appears to be a feasible and effective treatment method for patients with hepatorenal involvement of AE or CE.It fulfills the management criteria for advanced AE or CE cases,aiming to maximize patient benefits.
基金supported by the National Key Research and Development Program of China(No.2021YFC3201505-02)Shenzhen Science and Technology Plan Collaborative Innovation Project-Undertake Major National Science and Technology Projects of China(No.CJGJZD2020061710260200).
文摘Heterotrophic denitrification based on polylactic acid(PLAHD)can remove nitrate effectively,but it is expensive and can't remove phosphate.Autotrophic denitrification based on iron sulfide(ISAD)can simultaneously remove nitrate and phosphate cost-effectively,but its nitrate rate is slow.So,iron sulfide mineral/polylactic acid mixotrophic biofilter(ISPLAB)was constructed to combine advantages of ISAD and PLAHD.ISPLAB achieved nitrogen and phosphorus removal rates of 98.04%and 94.12%,respectively,at a hydraulic retention time(HRT)of 24 h.The study also revealed that controlling molecular weight(MW)of PLA improved the release of soluble organic matter;adding iron sulfide enhanced the hydrolysis of PLA and precipitated PO_(4)^(3-) of Fe^(2+)/Fe^(3+),thereby facilitated simultaneous nitrogen and phosphorus removal.Microbial community analysis resulted that denitrifying bacterias(Phaeodactylibacter and Methylotenera),sulfur-reducing bacterias(Hyphomicrobium),sulfur-oxidizing bacteria(Denitratisoma),iron-reducing bacteria(Romboutsia)and hydrolyzed bacterias(norank_f_norank_o_1-20 and norank_f_Caldilineaceae)coexisted in the ISPLAB system.Organics and iron sulfide drived the denitrification process in ISPLAB.
基金co-supported by the National Key Research and Development Program of China(No.2022YFF0503100)the Youth Innovation Project of Pandeng Program of National Space Science Center,Chinese Academy of Sciences(No.E3PD40012S).
文摘As we look ahead to future lunar exploration missions, such as crewed lunar exploration and establishing lunar scientific research stations, the lunar rovers will need to cover vast distances. These distances could range from kilometers to tens of kilometers, and even hundreds and thousands of kilometers. Therefore, it is crucial to develop effective long-range path planning for lunar rovers to meet the demands of lunar patrol exploration. This paper presents a hierarchical map model path planning method that utilizes the existing high-resolution images, digital elevation models and mineral abundance maps. The objective is to address the issue of the construction of lunar rover travel costs in the absence of large-scale, high-resolution digital elevation models. This method models the reference and semantic layers using the middle- and low-resolution remote sensing data. The multi-scale obstacles on the lunar surface are extracted by combining the deep learning algorithm on the high-resolution image, and the obstacle avoidance layer is modeled. A two-stage exploratory path planning decision is employed for long-distance driving path planning on a global–local scale. The proposed method analyzes the long-distance accessibility of various areas of scientific significance, such as Rima Bode. A high-precision digital elevation model is created using stereo images to validate the method. Based on the findings, it can be observed that the entire route spans a distance of 930.32 km. The route demonstrates an impressive ability to avoid meter-level impact craters and linear structures while maintaining an average slope of less than 8°. This paper explores scientific research by traversing at least seven basalt units, uncovering the secrets of lunar volcanic activities, and establishing ‘golden spike’ reference points for lunar stratigraphy. The final result of path planning can serve as a valuable reference for the design, mission demonstration, and subsequent project implementation of the new manned lunar rover.
基金supported by the Fund of Key Laboratory of Biomedical Engineering of Hainan Province(No.BME20240001)the STI2030-Major Projects(No.2021ZD0200104)the National Natural Science Foundations of China under Grant 61771437.
文摘Deep learning networks are increasingly exploited in the field of neuronal soma segmentation.However,annotating dataset is also an expensive and time-consuming task.Unsupervised domain adaptation is an effective method to mitigate the problem,which is able to learn an adaptive segmentation model by transferring knowledge from a rich-labeled source domain.In this paper,we propose a multi-level distribution alignment-based unsupervised domain adaptation network(MDA-Net)for segmentation of 3D neuronal soma images.Distribution alignment is performed in both feature space and output space.In the feature space,features from different scales are adaptively fused to enhance the feature extraction capability for small target somata and con-strained to be domain invariant by adversarial adaptation strategy.In the output space,local discrepancy maps that can reveal the spatial structures of somata are constructed on the predicted segmentation results.Then thedistribution alignment is performed on the local discrepancies maps across domains to obtain a superior discrepancy map in the target domain,achieving refined segmentation performance of neuronal somata.Additionally,after a period of distribution align-ment procedure,a portion of target samples with high confident pseudo-labels are selected as training data,which assist in learning a more adaptive segmentation network.We verified the superiority of the proposed algorithm by comparing several domain adaptation networks on two 3D mouse brain neuronal somata datasets and one macaque brain neuronal soma dataset.
文摘Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to various factors,including scattering noise,low contrast,and limited resolution in ultrasound images.Although existing segmentation models have made progress,they still suffer from several limitations,such as high error rates,low generalizability,overfitting,limited feature learning capability,etc.To address these challenges,this paper proposes a Multi-level Relation Transformer-based U-Net(MLRT-UNet)to improve thyroid nodule segmentation.The MLRTUNet leverages a novel Relation Transformer,which processes images at multiple scales,overcoming the limitations of traditional encoding methods.This transformer integrates both local and global features effectively through selfattention and cross-attention units,capturing intricate relationships within the data.The approach also introduces a Co-operative Transformer Fusion(CTF)module to combine multi-scale features from different encoding layers,enhancing the model’s ability to capture complex patterns in the data.Furthermore,the Relation Transformer block enhances long-distance dependencies during the decoding process,improving segmentation accuracy.Experimental results showthat the MLRT-UNet achieves high segmentation accuracy,reaching 98.2% on the Digital Database Thyroid Image(DDT)dataset,97.8% on the Thyroid Nodule 3493(TG3K)dataset,and 98.2% on the Thyroid Nodule3K(TN3K)dataset.These findings demonstrate that the proposed method significantly enhances the accuracy of thyroid nodule segmentation,addressing the limitations of existing models.
基金supported by the National Natural Science Foundation of China(Nos.21874060 and 22174058,U21A20282)the Science and Technology program of Gansu Province(No.22JR5RA476)。
文摘DNA repair enzymes are important in the repair of DNA lesions for maintaining the genome stability,and their abnormal expression induced various human cancers.Simultaneous detection of these DNA enzymes could provide convincing evidence based on the comparison of the activity of multiple enzymes than on that of single enzyme.Although fluorescence approach has been applied for the simultaneous detection both of DNA repair enzymes,the spectral overlap and multiwavelength excitation severely restrict the number of available fluorophores.Thus,it is difficult to simultaneously detect three enzymes in a single analysis by fluorescence detection.Herein,we developed a method for the simultaneous determination of three DNA repair enzymes including human flap DNA endonuclease 1(FEN1),human alkyladenine DNA glycosylase(hAAG)and uracil DNA glycosylase(UDG)based on the combination of template-free amplification system with capillary electrophoresis-laser induced fluorescence(CE-LIF)detection.The amplification system was adopted to transfer and amplify the enzymatic products into different length DNA fragments which could be separated effectively by CE-LIF without the complicated modification of the capillary inner wall or labeling different tails on signal probes for separation.The method demonstrated a detection limit of 0.07 U/mL(0.08-160 U/mL)for FEN1,2.40 U/mL(2.5-250U/mL)for hAAG and 2.1×10^(-4)U/mL(0.0004-2.5 U/mL)for UDG,the relative standard deviations(RSDs)of peak time and peak area for different analytes were as follows:2.50%-4,37%and 3.24%-7.18%(inter-day);1.37%-2.71%and 1.43%-3.02%(intra-day),4.28%-6.08%and 4.16%-7.57%(column to column),respectively.And it can identify the inhibitor-like drugs,evaluate enzymatic kinetics and achieve the detection of three enzymes in cell extracts,providing a simple and powerful platform for simultaneous detection of more DNA repair enzymes.
基金supported by the National Natural Science Foundation of China(42374134,42304125,U20B6005)the Science and Technology Commission of Shanghai Municipality(23JC1400502)the Fundamental Research Funds for the Central Universities.
文摘Blended acquisition offers efficiency improvements over conventional seismic data acquisition, at the cost of introducing blending noise effects. Besides, seismic data often suffers from irregularly missing shots caused by artificial or natural effects during blended acquisition. Therefore, blending noise attenuation and missing shots reconstruction are essential for providing high-quality seismic data for further seismic processing and interpretation. The iterative shrinkage thresholding algorithm can help obtain deblended data based on sparsity assumptions of complete unblended data, and it characterizes seismic data linearly. Supervised learning algorithms can effectively capture the nonlinear relationship between incomplete pseudo-deblended data and complete unblended data. However, the dependence on complete unblended labels limits their practicality in field applications. Consequently, a self-supervised algorithm is presented for simultaneous deblending and interpolation of incomplete blended data, which minimizes the difference between simulated and observed incomplete pseudo-deblended data. The used blind-trace U-Net (BTU-Net) prevents identity mapping during complete unblended data estimation. Furthermore, a multistep process with blending noise simulation-subtraction and missing traces reconstruction-insertion is used in each step to improve the deblending and interpolation performance. Experiments with synthetic and field incomplete blended data demonstrate the effectiveness of the multistep self-supervised BTU-Net algorithm.
文摘This paper addresses the Multi-Vehicle Routing Problem with Time Windows and Simultaneous Pickup and Delivery(MVRPTWSPD),aiming to optimize logistics distribution routes and minimize total costs.A vehicle routing optimization model is developed based on the operational requirements of the KS Logistics Center,focusing on minimizing vehicle dispatch,loading and unloading,operating,and time window penalty costs.The model incorporates constraints such as vehicle capacity,time windows,and travel distance,and is solved using a genetic algorithm to ensure optimal route planning.Through MATLAB simulations,34 customer points are analyzed,demonstrating that the simultaneous pickup and delivery model reduces total costs by 30.13%,increases vehicle loading rates by 20.04%,and decreases travel distance compared to delivery-only or pickup-only models.The results demonstrate the significant advantages of the simultaneous pickup and delivery mode in reducing logistics costs and improving vehicle utilization,offering valuable insights for enhancing the operational efficiency of the KS Logistics Center.
