In recent years,with the rapid development of deep learning technology,relational triplet extraction techniques have also achieved groundbreaking progress.Traditional pipeline models have certain limitations due to er...In recent years,with the rapid development of deep learning technology,relational triplet extraction techniques have also achieved groundbreaking progress.Traditional pipeline models have certain limitations due to error propagation.To overcome the limitations of traditional pipeline models,recent research has focused on jointly modeling the two key subtasks-named entity recognition and relation extraction-within a unified framework.To support future research,this paper provides a comprehensive review of recently published studies in the field of relational triplet extraction.The review examines commonly used public datasets for relational triplet extraction techniques and systematically reviews current mainstream joint extraction methods,including joint decoding methods and parameter sharing methods,with joint decoding methods further divided into table filling,tagging,and sequence-to-sequence approaches.In addition,this paper also conducts small-scale replication experiments on models that have performed well in recent years for each method to verify the reproducibility of the code and to compare the performance of different models under uniform conditions.Each method has its own advantages in terms of model design,task handling,and application scenarios,but also faces challenges such as processing complex sentence structures,cross-sentence relation extraction,and adaptability in low-resource environments.Finally,this paper systematically summarizes each method and discusses the future development prospects of joint extraction of relational triples.展开更多
The study introduces eco-friendly leaching agents as alternatives to traditional rare earth element(REE)extraction solvents,addressing environmental concerns associated with ammonium sulfate.Bio-based ionic liquids(IL...The study introduces eco-friendly leaching agents as alternatives to traditional rare earth element(REE)extraction solvents,addressing environmental concerns associated with ammonium sulfate.Bio-based ionic liquids(ILs),known for their non-toxic and biodegradable properties,were screened using the COSMO-RS software.Initially,105 ILs involving 7 cations and 15 anions were computationally screened to find the best ILs for REE extraction.The chosen criteria were based on hydrogen bond formation,affinity screening,hydrophobicity,viscosity,and eco-toxicity test.Based on the COSMO-RS screening,choline oleate,choline decanoate,and choline hexanoate exhibit high solubility for REEs,with a chemical potential of 17.60,17.01,and 18.37 kcal/mol at REE oxidation state+2.Choline glycinate,choline oleate,choline decanoate,choline hexanoate,choline lysinate,and choline leucinate were selected for their strong affinity to extract REE dissociate ions.Experimental results show slightly higher REE extraction from ammonium sulfate(3.17 ppm)compared to choline glycinate(3.15 ppm).For long-term applications,choline glycinate offers a promising eco-friendly and cost-effective alternative to traditional leaching agents,promoting economic feasibility and environmental friendliness.展开更多
Studying various aurora morphology helps us understand space's physical processes and the mechanisms behind these patterns.Auroral arcs are the brightest and most prominent auroral patterns.Due to the difficulty i...Studying various aurora morphology helps us understand space's physical processes and the mechanisms behind these patterns.Auroral arcs are the brightest and most prominent auroral patterns.Due to the difficulty in precisely defining auroral shape edges,auroral arc skeleton extraction is expected as an alternative representation for studying auroral morphology,resorting skeletons extract key morphological features from complex auroral shapes.Transformer models provide a better understanding of the relationship between the overall morphology and the details when processing image data,so we proposed a Transformer-based method for auroral arc skeleton extraction.Combined with ridge-guided annotation on all-sky images,a Transformer-based skeleton extractor is trained and used to estimate the number of auroral arcs.Experiments demonstrate that the Transformer-based model can more effectively capture structural information and local details of auroral arcs,which is suitable for complex auroral morphologies.展开更多
Bio-oil is a renewable fuel that can be obtained from biomass waste,such as empty palm fruit bunches,sugarcane bagasse,and rice husks.Within a biorefinery framework,bio-oil had not met the standards as a fuel due to t...Bio-oil is a renewable fuel that can be obtained from biomass waste,such as empty palm fruit bunches,sugarcane bagasse,and rice husks.Within a biorefinery framework,bio-oil had not met the standards as a fuel due to the presence of impurities like corrosive phenol.Therefore,the separation of phenol from bio-oil is essential and can be achieved using the extraction method.In this study,biomass wastes(empty fruit bunches of oil palm,sugarcane bagasse,and rice husk)were pyrolyzed in a biorefinery framework to produce bio-oil,which was then refined through liquid-liquid extraction with a methanol-chloroform and ethyl acetate solvents to remove its phenolic compound.The extraction with methanol-chloroform solvent was carried out for 1 h at 50℃.Meanwhile,extraction with ethyl acetate solvent was carried out for 3 h at 70℃.Both extractions used the same variations,i.e.,bio-oil:solvent ratio at 1:1,1:2,1:3,and 1:4,and stirring speeds of 150 rpm,200 rpm,250 rpm,and 300 rpm.The bio-oil obtained from this study contained complex chemical compounds and had characteristics such as a pH of 5,a density of 1.116 g/mL,and a viscosity of 29.57 cSt.Theoptimization results using response surface methodology(RSM)showed that the best yield formethanolchloroform was 72.98%at a stirring speed of 250 rpm and a ratio of 1:3.As for ethyl acetate solvent,the highest yield obtained was 71.78%at a stirring speed of 237.145 rpm and a ratio of 1:2.展开更多
This work uses advanced remote sensing to precisely extract hydrological information,supporting transmission network planning.High-resolution water body mapping lets designers optimize routes to avoid ecologically sen...This work uses advanced remote sensing to precisely extract hydrological information,supporting transmission network planning.High-resolution water body mapping lets designers optimize routes to avoid ecologically sensitive areas,achieving environmental protection,cost efficiency,and enhanced operational safety.The methodology provides a scalable,replicable framework for intelligent obstacle avoidance in power grid development,applicable to other regions and sectors with similar planning needs.展开更多
The development of new and efficient extractants plays a key role in the separation and recovery of rare earth elements.In this pape r,the extractant(N,N-methyl py ridineethyl-N',N'-dicyclohexyl-3-oxadiglycola...The development of new and efficient extractants plays a key role in the separation and recovery of rare earth elements.In this pape r,the extractant(N,N-methyl py ridineethyl-N',N'-dicyclohexyl-3-oxadiglycolamide,MPyEDChDGA) with a new structure was synthesized,and the pyridine group was successfully grafted onto the 3-oxadiglycolamide structure.Using MPyEDChDGA for efficient enrichment of rare earth ions,the self-assembled solids were recovered by simple filtration without further backextraction and final precipitation,achieving a one-step strategy for the recovery of rare earth ions.Several important parameters affecting the self-assembly extraction,including pH,diluent,temperature,and extractant concentration,were systematically evaluated using La(NO_(3))_(3),Tb(NO_(3))_(3),and Lu(NO_(3))_(3) as representatives.The self-assembled solids were investigated in detail by X-ray diffraction(XRD),scanning electron microscopy(SEM),1H nuclear magnetic resonance(1H NMR),Fourier transform infrared spectroscopy(FT-IR),Raman,and X-ray photoelectron spectroscopy(XPS) analyses.The stoichiometry of the extraction species was characterized using the Job's method and electrospray ionization mass spectrometry(ESI-MS).In addition,MPyEDChDGA was applied to the recovery of Sm in SmCoCu simulated liquid,and the results show that MPyEDChDGA has good selectivity of Sm from transition metals(Co,Cu).The separation factor of Sm/Co can reach 6281±117,which provides a new approach to recovering Sm from SmCoCu scrap magnets.This study presents an efficient and convenient new strategy for the recovery and separation of rare earth elements.展开更多
Web data extraction has become a key technology for extracting valuable data from websites.At present,most extraction methods based on rule learning,visual pattern or tree matching have limited performance on complex ...Web data extraction has become a key technology for extracting valuable data from websites.At present,most extraction methods based on rule learning,visual pattern or tree matching have limited performance on complex web pages.Through ana-lyzing various statistical characteristics of HTML el-ements in web documents,this paper proposes,based on statistical features,an unsupervised web data ex-traction method—traversing the HTML DOM parse tree at first,calculating and generating the statistical matrix of the elements,and then locating data records by clustering method and heuristic rules that reveal in-herent links between the visual characteristics of the data recording areas and the statistical characteristics of the HTML nodes—which is both suitable for data records extraction of single-page and multi-pages,and it has strong generality and needs no training.The ex-periments show that the accuracy and efficiency of this method are equally better than the current data extrac-tion method.展开更多
This study proposes a multi-scene smoke detection algorithm based on a multi-feature extraction method to address the problems of varying smoke shapes in different scenes,difficulty in locating and detecting transluce...This study proposes a multi-scene smoke detection algorithm based on a multi-feature extraction method to address the problems of varying smoke shapes in different scenes,difficulty in locating and detecting translucent smoke,and variable smoke scales.First,the convolution module of feature extraction in YOLOv5s backbone network is replaced with asymmetric convolution block re-parameterization convolution to improve the detection of different shapes of smoke.Then,coordinate attention mechanism is introduced in the deeper layer of the backbone network to further improve the localization of translucent smoke.Finally,the detection of smoke at different scales is further improved by using the feature pyramid convolution module instead of the standard convolution module of the feature pyramid in the model.The experimental results demonstrate the feasibility and superiority of the proposed model for multi-scene smoke detection.展开更多
The traditional EnFCM(Enhanced fuzzy C-means)algorithm only considers the grey-scale features in image segmentation,resulting in less than satisfactory results when the algorithm is used for remote sensing woodland im...The traditional EnFCM(Enhanced fuzzy C-means)algorithm only considers the grey-scale features in image segmentation,resulting in less than satisfactory results when the algorithm is used for remote sensing woodland image segmentation and extraction.An EnFCM remote sensing forest land extraction method based on PCA multi-feature fusion was proposed.Firstly,histogram equalization was applied to improve the image contrast.Secondly,the texture and edge features of the image were extracted,and a multi-feature fused pixel image was generated using the PCA technique.Moreover,the fused feature was used as a feature constraint to measure the difference of pixels instead of a single grey-scale feature.Finally,an improved feature distance metric calculated the similarity between the pixel points and the cluster center to complete the cluster segmentation.The experimental results showed that the error was between 1.5%and 4.0%compared with the forested area counted by experts’hand-drawing,which could obtain a high accuracy segmentation and extraction result.展开更多
In order to avoid the waste of iron caused by the direct use of ferronickel slag(FNS)in building materials,the effects of reduction iron extraction on the physical and chemical properties,cementitious reactivity and h...In order to avoid the waste of iron caused by the direct use of ferronickel slag(FNS)in building materials,the effects of reduction iron extraction on the physical and chemical properties,cementitious reactivity and hydration reaction characteristics of FNS and ferrum extraction tailing of nickel slag(FETNS)were studied.The experimental results show that the reduction ferrum extraction method changes the mineral phase composition of the waste slag,breaks the Si-O-Si bond,forms the tetrahedral structure of Si-O-NBO or Si-O-2NBO,and increases the content of active components such as Ca,Si,Mg,and Al.Compared with FNS,the 28 d compressive strength of pastes prepared by FETNS increases by 16.12%,22.57%,33.13%,44.26%,and 57.65%,respectively.The degree of hydration reaction of the composite cementitious systems in the FETNS group is higher than that in the FNS group at different ages,and the content of hydration products such as C-S-H gel and ettringite(AFt)is also higher than that in the FNS group.More hydration products can improve the curing ability to Cr and Mn of the composite cementitious systems in the FETNS group,and reduce the leaching value of Cr and Mn.展开更多
Given the scarcity of Satellite Frequency and Orbit(SFO)resources,it holds paramount importance to establish a comprehensive knowledge graph of SFO field(SFO-KG)and employ knowledge reasoning technology to automatical...Given the scarcity of Satellite Frequency and Orbit(SFO)resources,it holds paramount importance to establish a comprehensive knowledge graph of SFO field(SFO-KG)and employ knowledge reasoning technology to automatically mine available SFO resources.An essential aspect of constructing SFO-KG is the extraction of Chinese entity relations.Unfortunately,there is currently no publicly available Chinese SFO entity Relation Extraction(RE)dataset.Moreover,publicly available SFO text data contain numerous NA(representing for“No Answer”)relation category sentences that resemble other relation sentences and pose challenges in accurate classification,resulting in low recall and precision for the NA relation category in entity RE.Consequently,this issue adversely affects both the accuracy of constructing the knowledge graph and the efficiency of RE processes.To address these challenges,this paper proposes a method for extracting Chinese SFO text entity relations based on dynamic integrated learning.This method includes the construction of a manually annotated Chinese SFO entity RE dataset and a classifier combining features of SFO resource data.The proposed approach combines integrated learning and pre-training models,specifically utilizing Bidirectional Encoder Representation from Transformers(BERT).In addition,it incorporates one-class classification,attention mechanisms,and dynamic feedback mechanisms to improve the performance of the RE model.Experimental results show that the proposed method outperforms the traditional methods in terms of F1 value when extracting entity relations from both balanced and long-tailed datasets.展开更多
AIM:To evaluate the effect of femtosecond laser small incision lenticule extraction(SMILE)on the binocular visual function in myopic patients with glasses-free threedimensional(3D)technique.METHODS:Totally 50 myopic p...AIM:To evaluate the effect of femtosecond laser small incision lenticule extraction(SMILE)on the binocular visual function in myopic patients with glasses-free threedimensional(3D)technique.METHODS:Totally 50 myopic patients(39 females and 11 males)with SMILE were enrolled in this prospective study.The glasses-free 3D technique was used to evaluate the binocular visual function in these subjects including static stereopsis,dynamic stereopsis,foveal suppression,and binocular balance point of signal to noise ratio(s/n ratio).All subjects received measurements in 1d before operation,and 1d,1wk,and 1mo postoperatively.RESULTS:Both static and dynamic stereopsis showed no significant difference after SMILE.The foveal suppression improved significantly 1wk and 1mo after SMILE(P=0.005 and P=0.007 respectively).The binocular balance point of signal to noise ratio showed a significant improvement 1d,1wk and 1mo after SMILE for both eyes(P<0.001 for each eye respectively).CONCLUSION:Glasses-free 3D technique can be used to evaluate the effect of SMILE on the binocular visual function in myopic patients perceptively,and SMILE can improve both foveal suppression and binocular imbalance in these patients.展开更多
Real-time detection of surface defects on cables is crucial for ensuring the safe operation of power systems.However,existing methods struggle with small target sizes,complex backgrounds,low-quality image acquisition,...Real-time detection of surface defects on cables is crucial for ensuring the safe operation of power systems.However,existing methods struggle with small target sizes,complex backgrounds,low-quality image acquisition,and interference from contamination.To address these challenges,this paper proposes the Real-time Cable Defect Detection Network(RC2DNet),which achieves an optimal balance between detection accuracy and computational efficiency.Unlike conventional approaches,RC2DNet introduces a small object feature extraction module that enhances the semantic representation of small targets through feature pyramids,multi-level feature fusion,and an adaptive weighting mechanism.Additionally,a boundary feature enhancement module is designed,incorporating boundary-aware convolution,a novel boundary attention mechanism,and an improved loss function to significantly enhance boundary localization accuracy.Experimental results demonstrate that RC2DNet outperforms state-of-the-art methods in precision,recall,F1-score,mean Intersection over Union(mIoU),and frame rate,enabling real-time and highly accurate cable defect detection in complex backgrounds.展开更多
Biomineralization based on bacterial enzyme induced carbonate precipitation(BEICP)process is a promising alternative to cement-based ground treatment technology.The bacterial urease used in BEICP process is usually ul...Biomineralization based on bacterial enzyme induced carbonate precipitation(BEICP)process is a promising alternative to cement-based ground treatment technology.The bacterial urease used in BEICP process is usually ultrasonic extracted from urease-producing bacteria.To efficiently extract urease with relatively higher activity from bacterial cells,the ultrasonic extraction parameters of urease were optimized in this study.Next,a series of bacterial urease extraction tests and sand column treatment tests were conducted to investigate the effects of vibration amplitude,upper temperature limit,and cooling method on the urease extraction process and biomineralization of sand.The results show that the upper temperature limit is an important factor affecting the extraction efficiency and the activity of the extracted urease solution,and the optimum upper temperature limit is 50℃.The results indicate that increasing vibration amplitude could improve the extraction efficiency,but it hardly affects the urease activity(UA)under the optimal temperature.Continuous cooling could effectively simplify the operation and further improve the efficiency of urease extraction.Under the same urease activity of biotreatment solution,there is no marked difference in calcium carbonate content(CCC)and unconfined compressive strength of biomineralized sand columns prepared by urease solution extracted with different vibration amplitudes and upper temperature limits.The results of this study could provide a reference for application of BEICP technology of urease extraction to large-scale soil treatment.展开更多
Purpose–This study aims to enhance the accuracy of key entity extraction from railway accident report texts and address challenges such as complex domain-specific semantics,data sparsity and strong inter-sentence sem...Purpose–This study aims to enhance the accuracy of key entity extraction from railway accident report texts and address challenges such as complex domain-specific semantics,data sparsity and strong inter-sentence semantic dependencies.A robust entity extraction method tailored for accident texts is proposed.Design/methodology/approach–This method is implemented through a dual-branch multi-task mutual learning model named R-MLP,which jointly performs entity recognition and accident phase classification.The model leverages a shared BERT encoder to extract contextual features and incorporates a sentence span indexing module to align feature granularity.A cross-task mutual learning mechanism is also introduced to strengthen semantic representation.Findings–R-MLP effectively mitigates the impact of semantic complexity and data sparsity in domain entities and enhances the model’s ability to capture inter-sentence semantic dependencies.Experimental results show that R-MLP achieves a maximum F1-score of 0.736 in extracting six types of key railway accident entities,significantly outperforming baseline models such as RoBERTa and MacBERT.Originality/value–This demonstrates the proposed method’s superior generalization and accuracy in domainspecific entity extraction tasks,confirming its effectiveness and practical value.展开更多
The effects of styrene-butadiene-styrene(SBS)pre-swelling/extraction process and the incorporation of C9 petroleum resin on the anti-aging performance of modified asphalt were systematically evaluated by characterizin...The effects of styrene-butadiene-styrene(SBS)pre-swelling/extraction process and the incorporation of C9 petroleum resin on the anti-aging performance of modified asphalt were systematically evaluated by characterizing the physical indexes,chemical compositions and rheological parameters.The experimental results show that the SBS pre-swelling/extraction process and the incorporation of C9 petroleum resin improve the dispersion performance of SBS in asphalt as well as the strength of SBS polymer network structures,and the synergistic effects decrease the volatilization degree of asphalt lightweight components and the degradation rate of SBS during the aging process.The anti-aging performance of SBS modified asphalt(SBSMA)was significantly enhanced by SBS pre-swelling/extraction process compounded with the incorporation of C9 petroleum resin,and the anti-aging effect was gradually enhanced with the increase of C9 petroleum resin content.展开更多
The success of robot-assisted pelvic fracture reduction surgery heavily relies on the accuracy of 3D/3D feature-based registration.This process involves extracting anatomical feature points from pre-operative 3D image...The success of robot-assisted pelvic fracture reduction surgery heavily relies on the accuracy of 3D/3D feature-based registration.This process involves extracting anatomical feature points from pre-operative 3D images which can be challenging because of the complex and variable structure of the pelvis.PointMLP_RegNet,a modified PointMLP,was introduced to address this issue.It retains the feature extraction module of PointMLP but replaces the classification layer with a regression layer to predict the coordinates of feature points instead of conducting regular classification.A flowchart for an automatic feature points extraction method was presented,and a series of experiments was conducted on a clinical pelvic dataset to confirm the accuracy and effectiveness of the method.PointMLP_RegNet extracted feature points more accurately,with 8 out of 10 points showing less than 4 mm errors and the remaining two less than 5 mm.Compared to PointNettt and PointNet,it exhibited higher accuracy,robustness and space efficiency.The proposed method will improve the accuracy of anatomical feature points extraction,enhance intra-operative registration precision and facilitate the widespread clinical application of robot-assisted pelvic fracture reduction.展开更多
In order to realize the full resource utilization of ferronickel slag(FNS)in cement-based materials,this paper studied the influences of mechanical grinding activation on the physical and chemical properties and react...In order to realize the full resource utilization of ferronickel slag(FNS)in cement-based materials,this paper studied the influences of mechanical grinding activation on the physical and chemical properties and reactivity of ferrous extraction tailing of nickel slag(FETNS).Four grinding processes of 5,10,20 and 30 min were set up to evaluate the influence of grinding process on the physical and chemical properties of FETNS with the aid of BET,XRD,Rietveld analysis and particle size distribution.The cement-FETNS composite cementitious material was prepared by replacing cement with 0%,10%,15%,20%,25%and 30%FETNS.The influence of FETNS fineness and content on the properties of composite cementitious system were characterized by mechanical properties,reaction products,early hydration process and pore structure characteristics.The results show that the grinding process can effectively improve the pozzolanic activity of FETNS.The compressive strength of FETNS-M_(30)paste is higher than that of FETNS-M_(5) paste in the early and late stages,and the later strength is higher than that of the baseline group when the content of FETNS-M_(30)is 10%-25%.The pozzolanic activity of FETNS-M_(30)powder is significantly improved and higher than that of FETNS-M_(5) powder.Under the same content,the Ca/Si ratio of C-S-H gel in FETNS-M_(30)paste is small,and the degree of silicate polymerization is higher.When the FETNS-M_(30)content is 10%,the proportions of favorable pores d<50 nm(harmless pores and less-harmful pores)of FETNS-M_(5) paste and FETNS-M_(30)paste is 95.3%and 95.4%,respectively,indicating a denser pore structure of the FETNS-M_(30)paste.展开更多
In the management of land resources and the protection of cultivated land,the law enforcement of land satellite images is often used as one of the main means.In recent years,the policies and regulations of the law enf...In the management of land resources and the protection of cultivated land,the law enforcement of land satellite images is often used as one of the main means.In recent years,the policies and regulations of the law enforcement of land satellite images have become more and more strict and been adjusted increasingly frequently,playing a decisive role in preventing excessive non-agricultural and non-food urbanization.In the process of the law enforcement,the extraction of suspected illegal buildings is the most important and time-consuming content.Compared with the traditional deep learning model,fully convolutional networks(FCN)has a great advantage in remote sensing image processing because its input images are not limited by size,and both convolution and deconvolution are independent of the overall size of images.In this paper,an intelligent extraction model of suspected illegal buildings from land satellite images based on deep learning FCN was built.Kaiyuan City,Yunnan Province was taken as an example.The verification results show that the global accuracy of this model was 86.6%in the process of building extraction,and mean intersection over union(mIoU)was 73.6%.This study can provide reference for the extraction of suspected illegal buildings in the law enforcement work of land satellite images,and reduce the tedious manual operation to a certain extent.展开更多
基金funding from Key Areas Science and Technology Research Plan of Xinjiang Production And Construction Corps Financial Science and Technology Plan Project under Grant Agreement No.2023AB048 for the project:Research and Application Demonstration of Data-driven Elderly Care System.
文摘In recent years,with the rapid development of deep learning technology,relational triplet extraction techniques have also achieved groundbreaking progress.Traditional pipeline models have certain limitations due to error propagation.To overcome the limitations of traditional pipeline models,recent research has focused on jointly modeling the two key subtasks-named entity recognition and relation extraction-within a unified framework.To support future research,this paper provides a comprehensive review of recently published studies in the field of relational triplet extraction.The review examines commonly used public datasets for relational triplet extraction techniques and systematically reviews current mainstream joint extraction methods,including joint decoding methods and parameter sharing methods,with joint decoding methods further divided into table filling,tagging,and sequence-to-sequence approaches.In addition,this paper also conducts small-scale replication experiments on models that have performed well in recent years for each method to verify the reproducibility of the code and to compare the performance of different models under uniform conditions.Each method has its own advantages in terms of model design,task handling,and application scenarios,but also faces challenges such as processing complex sentence structures,cross-sentence relation extraction,and adaptability in low-resource environments.Finally,this paper systematically summarizes each method and discusses the future development prospects of joint extraction of relational triples.
基金supported by Petronas Research Sdn Bhd(PRSB)with grant number(015M20-129)Centre of Research in Ionic Liquids(CORIL)Universiti Teknologi PETRONAS for the facilities and support provided。
文摘The study introduces eco-friendly leaching agents as alternatives to traditional rare earth element(REE)extraction solvents,addressing environmental concerns associated with ammonium sulfate.Bio-based ionic liquids(ILs),known for their non-toxic and biodegradable properties,were screened using the COSMO-RS software.Initially,105 ILs involving 7 cations and 15 anions were computationally screened to find the best ILs for REE extraction.The chosen criteria were based on hydrogen bond formation,affinity screening,hydrophobicity,viscosity,and eco-toxicity test.Based on the COSMO-RS screening,choline oleate,choline decanoate,and choline hexanoate exhibit high solubility for REEs,with a chemical potential of 17.60,17.01,and 18.37 kcal/mol at REE oxidation state+2.Choline glycinate,choline oleate,choline decanoate,choline hexanoate,choline lysinate,and choline leucinate were selected for their strong affinity to extract REE dissociate ions.Experimental results show slightly higher REE extraction from ammonium sulfate(3.17 ppm)compared to choline glycinate(3.15 ppm).For long-term applications,choline glycinate offers a promising eco-friendly and cost-effective alternative to traditional leaching agents,promoting economic feasibility and environmental friendliness.
基金supported by the National Natural Science Foundation of China(Grant no.41874173)。
文摘Studying various aurora morphology helps us understand space's physical processes and the mechanisms behind these patterns.Auroral arcs are the brightest and most prominent auroral patterns.Due to the difficulty in precisely defining auroral shape edges,auroral arc skeleton extraction is expected as an alternative representation for studying auroral morphology,resorting skeletons extract key morphological features from complex auroral shapes.Transformer models provide a better understanding of the relationship between the overall morphology and the details when processing image data,so we proposed a Transformer-based method for auroral arc skeleton extraction.Combined with ridge-guided annotation on all-sky images,a Transformer-based skeleton extractor is trained and used to estimate the number of auroral arcs.Experiments demonstrate that the Transformer-based model can more effectively capture structural information and local details of auroral arcs,which is suitable for complex auroral morphologies.
基金supported by theUniversitasNegeri Semarang throughDPAUNNES 2024The grant number is No.271.26.2/UN37/PPK.10/2024.
文摘Bio-oil is a renewable fuel that can be obtained from biomass waste,such as empty palm fruit bunches,sugarcane bagasse,and rice husks.Within a biorefinery framework,bio-oil had not met the standards as a fuel due to the presence of impurities like corrosive phenol.Therefore,the separation of phenol from bio-oil is essential and can be achieved using the extraction method.In this study,biomass wastes(empty fruit bunches of oil palm,sugarcane bagasse,and rice husk)were pyrolyzed in a biorefinery framework to produce bio-oil,which was then refined through liquid-liquid extraction with a methanol-chloroform and ethyl acetate solvents to remove its phenolic compound.The extraction with methanol-chloroform solvent was carried out for 1 h at 50℃.Meanwhile,extraction with ethyl acetate solvent was carried out for 3 h at 70℃.Both extractions used the same variations,i.e.,bio-oil:solvent ratio at 1:1,1:2,1:3,and 1:4,and stirring speeds of 150 rpm,200 rpm,250 rpm,and 300 rpm.The bio-oil obtained from this study contained complex chemical compounds and had characteristics such as a pH of 5,a density of 1.116 g/mL,and a viscosity of 29.57 cSt.Theoptimization results using response surface methodology(RSM)showed that the best yield formethanolchloroform was 72.98%at a stirring speed of 250 rpm and a ratio of 1:3.As for ethyl acetate solvent,the highest yield obtained was 71.78%at a stirring speed of 237.145 rpm and a ratio of 1:2.
基金The State Grid Independent Research and Development Project(Project No.:CY1124SHF02)National Natural Science Foundation of China(Project No.:52320105003)the Fundamental Research Funds for the Central Universities(Project No.:E3ET1803)。
文摘This work uses advanced remote sensing to precisely extract hydrological information,supporting transmission network planning.High-resolution water body mapping lets designers optimize routes to avoid ecologically sensitive areas,achieving environmental protection,cost efficiency,and enhanced operational safety.The methodology provides a scalable,replicable framework for intelligent obstacle avoidance in power grid development,applicable to other regions and sectors with similar planning needs.
基金Project supported by the Natural Science Foundation of Shandong Province (ZR2022QB067)。
文摘The development of new and efficient extractants plays a key role in the separation and recovery of rare earth elements.In this pape r,the extractant(N,N-methyl py ridineethyl-N',N'-dicyclohexyl-3-oxadiglycolamide,MPyEDChDGA) with a new structure was synthesized,and the pyridine group was successfully grafted onto the 3-oxadiglycolamide structure.Using MPyEDChDGA for efficient enrichment of rare earth ions,the self-assembled solids were recovered by simple filtration without further backextraction and final precipitation,achieving a one-step strategy for the recovery of rare earth ions.Several important parameters affecting the self-assembly extraction,including pH,diluent,temperature,and extractant concentration,were systematically evaluated using La(NO_(3))_(3),Tb(NO_(3))_(3),and Lu(NO_(3))_(3) as representatives.The self-assembled solids were investigated in detail by X-ray diffraction(XRD),scanning electron microscopy(SEM),1H nuclear magnetic resonance(1H NMR),Fourier transform infrared spectroscopy(FT-IR),Raman,and X-ray photoelectron spectroscopy(XPS) analyses.The stoichiometry of the extraction species was characterized using the Job's method and electrospray ionization mass spectrometry(ESI-MS).In addition,MPyEDChDGA was applied to the recovery of Sm in SmCoCu simulated liquid,and the results show that MPyEDChDGA has good selectivity of Sm from transition metals(Co,Cu).The separation factor of Sm/Co can reach 6281±117,which provides a new approach to recovering Sm from SmCoCu scrap magnets.This study presents an efficient and convenient new strategy for the recovery and separation of rare earth elements.
文摘Web data extraction has become a key technology for extracting valuable data from websites.At present,most extraction methods based on rule learning,visual pattern or tree matching have limited performance on complex web pages.Through ana-lyzing various statistical characteristics of HTML el-ements in web documents,this paper proposes,based on statistical features,an unsupervised web data ex-traction method—traversing the HTML DOM parse tree at first,calculating and generating the statistical matrix of the elements,and then locating data records by clustering method and heuristic rules that reveal in-herent links between the visual characteristics of the data recording areas and the statistical characteristics of the HTML nodes—which is both suitable for data records extraction of single-page and multi-pages,and it has strong generality and needs no training.The ex-periments show that the accuracy and efficiency of this method are equally better than the current data extrac-tion method.
基金the Natural Science Foundation of Zhejiang Province(Nos.LY20F020015 and LY21F020015)the National Natural Science Foundation of China(Nos.61972121 and 61902099)。
文摘This study proposes a multi-scene smoke detection algorithm based on a multi-feature extraction method to address the problems of varying smoke shapes in different scenes,difficulty in locating and detecting translucent smoke,and variable smoke scales.First,the convolution module of feature extraction in YOLOv5s backbone network is replaced with asymmetric convolution block re-parameterization convolution to improve the detection of different shapes of smoke.Then,coordinate attention mechanism is introduced in the deeper layer of the backbone network to further improve the localization of translucent smoke.Finally,the detection of smoke at different scales is further improved by using the feature pyramid convolution module instead of the standard convolution module of the feature pyramid in the model.The experimental results demonstrate the feasibility and superiority of the proposed model for multi-scene smoke detection.
基金supported by National Natural Science Foundation of China(No.61761027)Gansu Young Doctor’s Fund for Higher Education Institutions(No.2021QB-053)。
文摘The traditional EnFCM(Enhanced fuzzy C-means)algorithm only considers the grey-scale features in image segmentation,resulting in less than satisfactory results when the algorithm is used for remote sensing woodland image segmentation and extraction.An EnFCM remote sensing forest land extraction method based on PCA multi-feature fusion was proposed.Firstly,histogram equalization was applied to improve the image contrast.Secondly,the texture and edge features of the image were extracted,and a multi-feature fused pixel image was generated using the PCA technique.Moreover,the fused feature was used as a feature constraint to measure the difference of pixels instead of a single grey-scale feature.Finally,an improved feature distance metric calculated the similarity between the pixel points and the cluster center to complete the cluster segmentation.The experimental results showed that the error was between 1.5%and 4.0%compared with the forested area counted by experts’hand-drawing,which could obtain a high accuracy segmentation and extraction result.
基金Funded by the Science and Technology Program of Gansu Province(Nos.23JRRA799 and 24JRRA213)the National Natural Science Foundation of China(Nos.52178216,52008196,and U21A20150)。
文摘In order to avoid the waste of iron caused by the direct use of ferronickel slag(FNS)in building materials,the effects of reduction iron extraction on the physical and chemical properties,cementitious reactivity and hydration reaction characteristics of FNS and ferrum extraction tailing of nickel slag(FETNS)were studied.The experimental results show that the reduction ferrum extraction method changes the mineral phase composition of the waste slag,breaks the Si-O-Si bond,forms the tetrahedral structure of Si-O-NBO or Si-O-2NBO,and increases the content of active components such as Ca,Si,Mg,and Al.Compared with FNS,the 28 d compressive strength of pastes prepared by FETNS increases by 16.12%,22.57%,33.13%,44.26%,and 57.65%,respectively.The degree of hydration reaction of the composite cementitious systems in the FETNS group is higher than that in the FNS group at different ages,and the content of hydration products such as C-S-H gel and ettringite(AFt)is also higher than that in the FNS group.More hydration products can improve the curing ability to Cr and Mn of the composite cementitious systems in the FETNS group,and reduce the leaching value of Cr and Mn.
文摘Given the scarcity of Satellite Frequency and Orbit(SFO)resources,it holds paramount importance to establish a comprehensive knowledge graph of SFO field(SFO-KG)and employ knowledge reasoning technology to automatically mine available SFO resources.An essential aspect of constructing SFO-KG is the extraction of Chinese entity relations.Unfortunately,there is currently no publicly available Chinese SFO entity Relation Extraction(RE)dataset.Moreover,publicly available SFO text data contain numerous NA(representing for“No Answer”)relation category sentences that resemble other relation sentences and pose challenges in accurate classification,resulting in low recall and precision for the NA relation category in entity RE.Consequently,this issue adversely affects both the accuracy of constructing the knowledge graph and the efficiency of RE processes.To address these challenges,this paper proposes a method for extracting Chinese SFO text entity relations based on dynamic integrated learning.This method includes the construction of a manually annotated Chinese SFO entity RE dataset and a classifier combining features of SFO resource data.The proposed approach combines integrated learning and pre-training models,specifically utilizing Bidirectional Encoder Representation from Transformers(BERT).In addition,it incorporates one-class classification,attention mechanisms,and dynamic feedback mechanisms to improve the performance of the RE model.Experimental results show that the proposed method outperforms the traditional methods in terms of F1 value when extracting entity relations from both balanced and long-tailed datasets.
基金Supported by Sichuan Science and Technology Program(No.23NSFSC0856).
文摘AIM:To evaluate the effect of femtosecond laser small incision lenticule extraction(SMILE)on the binocular visual function in myopic patients with glasses-free threedimensional(3D)technique.METHODS:Totally 50 myopic patients(39 females and 11 males)with SMILE were enrolled in this prospective study.The glasses-free 3D technique was used to evaluate the binocular visual function in these subjects including static stereopsis,dynamic stereopsis,foveal suppression,and binocular balance point of signal to noise ratio(s/n ratio).All subjects received measurements in 1d before operation,and 1d,1wk,and 1mo postoperatively.RESULTS:Both static and dynamic stereopsis showed no significant difference after SMILE.The foveal suppression improved significantly 1wk and 1mo after SMILE(P=0.005 and P=0.007 respectively).The binocular balance point of signal to noise ratio showed a significant improvement 1d,1wk and 1mo after SMILE for both eyes(P<0.001 for each eye respectively).CONCLUSION:Glasses-free 3D technique can be used to evaluate the effect of SMILE on the binocular visual function in myopic patients perceptively,and SMILE can improve both foveal suppression and binocular imbalance in these patients.
基金supported by the National Natural Science Foundation of China under Grant 62306128the Basic Science Research Project of Jiangsu Provincial Department of Education under Grant 23KJD520003the Leading Innovation Project of Changzhou Science and Technology Bureau under Grant CQ20230072.
文摘Real-time detection of surface defects on cables is crucial for ensuring the safe operation of power systems.However,existing methods struggle with small target sizes,complex backgrounds,low-quality image acquisition,and interference from contamination.To address these challenges,this paper proposes the Real-time Cable Defect Detection Network(RC2DNet),which achieves an optimal balance between detection accuracy and computational efficiency.Unlike conventional approaches,RC2DNet introduces a small object feature extraction module that enhances the semantic representation of small targets through feature pyramids,multi-level feature fusion,and an adaptive weighting mechanism.Additionally,a boundary feature enhancement module is designed,incorporating boundary-aware convolution,a novel boundary attention mechanism,and an improved loss function to significantly enhance boundary localization accuracy.Experimental results demonstrate that RC2DNet outperforms state-of-the-art methods in precision,recall,F1-score,mean Intersection over Union(mIoU),and frame rate,enabling real-time and highly accurate cable defect detection in complex backgrounds.
基金the National Natural Science Foundation of China(NSFC)(Grant Nos.52108307 and 52178319)the Natural Science Foundation of Fujian Province,China(Grant No.2022J05020).
文摘Biomineralization based on bacterial enzyme induced carbonate precipitation(BEICP)process is a promising alternative to cement-based ground treatment technology.The bacterial urease used in BEICP process is usually ultrasonic extracted from urease-producing bacteria.To efficiently extract urease with relatively higher activity from bacterial cells,the ultrasonic extraction parameters of urease were optimized in this study.Next,a series of bacterial urease extraction tests and sand column treatment tests were conducted to investigate the effects of vibration amplitude,upper temperature limit,and cooling method on the urease extraction process and biomineralization of sand.The results show that the upper temperature limit is an important factor affecting the extraction efficiency and the activity of the extracted urease solution,and the optimum upper temperature limit is 50℃.The results indicate that increasing vibration amplitude could improve the extraction efficiency,but it hardly affects the urease activity(UA)under the optimal temperature.Continuous cooling could effectively simplify the operation and further improve the efficiency of urease extraction.Under the same urease activity of biotreatment solution,there is no marked difference in calcium carbonate content(CCC)and unconfined compressive strength of biomineralized sand columns prepared by urease solution extracted with different vibration amplitudes and upper temperature limits.The results of this study could provide a reference for application of BEICP technology of urease extraction to large-scale soil treatment.
基金funded by the Technology Research and Development Plan Program of China State Railway Group Co.,Ltd.(No.Q2024T001)the Foundation of China Academy of Railway Sciences Co.,Ltd.(No:2024YJ259).
文摘Purpose–This study aims to enhance the accuracy of key entity extraction from railway accident report texts and address challenges such as complex domain-specific semantics,data sparsity and strong inter-sentence semantic dependencies.A robust entity extraction method tailored for accident texts is proposed.Design/methodology/approach–This method is implemented through a dual-branch multi-task mutual learning model named R-MLP,which jointly performs entity recognition and accident phase classification.The model leverages a shared BERT encoder to extract contextual features and incorporates a sentence span indexing module to align feature granularity.A cross-task mutual learning mechanism is also introduced to strengthen semantic representation.Findings–R-MLP effectively mitigates the impact of semantic complexity and data sparsity in domain entities and enhances the model’s ability to capture inter-sentence semantic dependencies.Experimental results show that R-MLP achieves a maximum F1-score of 0.736 in extracting six types of key railway accident entities,significantly outperforming baseline models such as RoBERTa and MacBERT.Originality/value–This demonstrates the proposed method’s superior generalization and accuracy in domainspecific entity extraction tasks,confirming its effectiveness and practical value.
基金Fnded by the National Key Research and Development Program of China(No.2023YFC3807202)the Key Research and Development Plan in Hubei Province of China(Nos.2022BCA082 and 2024BAB108)the Annual Research Project of China Railway Construction Corporation(No.2023-B03)。
文摘The effects of styrene-butadiene-styrene(SBS)pre-swelling/extraction process and the incorporation of C9 petroleum resin on the anti-aging performance of modified asphalt were systematically evaluated by characterizing the physical indexes,chemical compositions and rheological parameters.The experimental results show that the SBS pre-swelling/extraction process and the incorporation of C9 petroleum resin improve the dispersion performance of SBS in asphalt as well as the strength of SBS polymer network structures,and the synergistic effects decrease the volatilization degree of asphalt lightweight components and the degradation rate of SBS during the aging process.The anti-aging performance of SBS modified asphalt(SBSMA)was significantly enhanced by SBS pre-swelling/extraction process compounded with the incorporation of C9 petroleum resin,and the anti-aging effect was gradually enhanced with the increase of C9 petroleum resin content.
基金supported by the National Key Research and Development Program of China(Grant No.2020YFB1313800)the National Science Foundation of China(Grant No.NSFC62373259)+1 种基金the Natural Science Foundation of Top Talent of SZTU(Grant No.GDRC202303)the Education Promotion Foundation of Guangdong Province(Grant No.2022ZDJS115).
文摘The success of robot-assisted pelvic fracture reduction surgery heavily relies on the accuracy of 3D/3D feature-based registration.This process involves extracting anatomical feature points from pre-operative 3D images which can be challenging because of the complex and variable structure of the pelvis.PointMLP_RegNet,a modified PointMLP,was introduced to address this issue.It retains the feature extraction module of PointMLP but replaces the classification layer with a regression layer to predict the coordinates of feature points instead of conducting regular classification.A flowchart for an automatic feature points extraction method was presented,and a series of experiments was conducted on a clinical pelvic dataset to confirm the accuracy and effectiveness of the method.PointMLP_RegNet extracted feature points more accurately,with 8 out of 10 points showing less than 4 mm errors and the remaining two less than 5 mm.Compared to PointNettt and PointNet,it exhibited higher accuracy,robustness and space efficiency.The proposed method will improve the accuracy of anatomical feature points extraction,enhance intra-operative registration precision and facilitate the widespread clinical application of robot-assisted pelvic fracture reduction.
基金Funded by the Science and Technology Program of Gansu Province(Nos.25CXGA070,24JRRA213)the National Natural Science Foundation of China(Nos.52468036,52178216,U21A20150)。
文摘In order to realize the full resource utilization of ferronickel slag(FNS)in cement-based materials,this paper studied the influences of mechanical grinding activation on the physical and chemical properties and reactivity of ferrous extraction tailing of nickel slag(FETNS).Four grinding processes of 5,10,20 and 30 min were set up to evaluate the influence of grinding process on the physical and chemical properties of FETNS with the aid of BET,XRD,Rietveld analysis and particle size distribution.The cement-FETNS composite cementitious material was prepared by replacing cement with 0%,10%,15%,20%,25%and 30%FETNS.The influence of FETNS fineness and content on the properties of composite cementitious system were characterized by mechanical properties,reaction products,early hydration process and pore structure characteristics.The results show that the grinding process can effectively improve the pozzolanic activity of FETNS.The compressive strength of FETNS-M_(30)paste is higher than that of FETNS-M_(5) paste in the early and late stages,and the later strength is higher than that of the baseline group when the content of FETNS-M_(30)is 10%-25%.The pozzolanic activity of FETNS-M_(30)powder is significantly improved and higher than that of FETNS-M_(5) powder.Under the same content,the Ca/Si ratio of C-S-H gel in FETNS-M_(30)paste is small,and the degree of silicate polymerization is higher.When the FETNS-M_(30)content is 10%,the proportions of favorable pores d<50 nm(harmless pores and less-harmful pores)of FETNS-M_(5) paste and FETNS-M_(30)paste is 95.3%and 95.4%,respectively,indicating a denser pore structure of the FETNS-M_(30)paste.
文摘In the management of land resources and the protection of cultivated land,the law enforcement of land satellite images is often used as one of the main means.In recent years,the policies and regulations of the law enforcement of land satellite images have become more and more strict and been adjusted increasingly frequently,playing a decisive role in preventing excessive non-agricultural and non-food urbanization.In the process of the law enforcement,the extraction of suspected illegal buildings is the most important and time-consuming content.Compared with the traditional deep learning model,fully convolutional networks(FCN)has a great advantage in remote sensing image processing because its input images are not limited by size,and both convolution and deconvolution are independent of the overall size of images.In this paper,an intelligent extraction model of suspected illegal buildings from land satellite images based on deep learning FCN was built.Kaiyuan City,Yunnan Province was taken as an example.The verification results show that the global accuracy of this model was 86.6%in the process of building extraction,and mean intersection over union(mIoU)was 73.6%.This study can provide reference for the extraction of suspected illegal buildings in the law enforcement work of land satellite images,and reduce the tedious manual operation to a certain extent.
