Standard bacterial suspensions play a crucial role in microbiological diagnosis.Traditional prepar-ation methods,which rely heavily on manual operations,face challenges such as poor reproducibility,low ef-ficiency,and...Standard bacterial suspensions play a crucial role in microbiological diagnosis.Traditional prepar-ation methods,which rely heavily on manual operations,face challenges such as poor reproducibility,low ef-ficiency,and biosafety concerns.In this study,we propose a high-precision automated colony extraction and separation system that combines large-field imaging and artificial intelligence(AI)to facilitate intelligent screening and localization of colonies.Firstly,a large-field imaging system was developed to capture high-resolution images of 90 mm Petri dishes,achieving a physical resolution of 13.2μm and an imaging speed of 13 frames per second.Subsequently,AI technology was employed for the automatic recognition and localiza-tion of colonies,enabling the selection of target colonies with diameters ranging from 1.9 to 2.3 mm.Next,a three-axis motion control platform was designed,accompanied by a path planning algorithm for the efficient extraction of colonies.An electronic pipette was employed for accurate colony collection.Additionally,a bacterial suspension concentration measurement module was developed,incorporating a 650 nm laser diode as the light source,achieving a measurement accuracy of 0.01 McFarland concentration(MCF).Finally,the system’s performance was validated through the preparation of an Esckerichia coli(E.coli)suspension.After 17 hours of cultivation,E.coli was extracted four times,achieving the target concentration set by the system.This work is expected to enable rapid and accurate microbial sample preparation,significantly reducing de-tection cycles and alleviating the workload of healthcare personnel.展开更多
The lack of macro-continuity and mechanical strength of covalent organic frameworks(COFs)has significantly limited their practical applications.Here,we propose an“alcohol-triggered defect cleavage”strategy to precis...The lack of macro-continuity and mechanical strength of covalent organic frameworks(COFs)has significantly limited their practical applications.Here,we propose an“alcohol-triggered defect cleavage”strategy to precisely regulate the growth and stacking of COF grains through a moderate reversed Schiff base reaction,realizing the direct synthesis of COF nanofibers(CNFs)with high aspect ratio(L/D=103.05)and long length(>20μm).An individual CNF exhibits a biomimetic scale-like architecture,achieving superior flexibility and fatigue resistance under dynamic bending via a multiscale stress dissipation mechanism.Taking advantages of these structural features,we engineer CNF aerogels(CNF-As)with programmable porous structures(e.g.,honeycomb,lamellar,isotropic)via directional ice-template methodology.CNF-As demonstrate 100%COF content,high specific surface area(396.15 m^(2)g^(-1))and superelasticity(~0%elastic deformation after 500 compression cycles at 50%strain),outperforming most COF-based counterparts.Compared with the conventional COF aerogels,the unique structural features of CNF-A enable it to perform outstandingly in uranium extraction,with an 11.72-fold increment in adsorption capacity(920.12 mg g^(-1))and adsorption rate(89.9%),and a 2.48-fold improvement in selectivity(U/V=2.31).This study provides a direct strategy for the development of next-generation COF materials with outstanding functionality and structural robustness.展开更多
As an important class of phenanthroline derivatives containing soft N and hard O donor atoms,the laborious syntheses of unsymmetrical 1,10-phenanthroline-derived diamide ligands(DAPhen) have hindered its extensive stu...As an important class of phenanthroline derivatives containing soft N and hard O donor atoms,the laborious syntheses of unsymmetrical 1,10-phenanthroline-derived diamide ligands(DAPhen) have hindered its extensive study.In this work,we first report a convenient synthetic method for the construction of DAPhen using Friedländer reaction by two facile steps(vs.previous 12 steps).A variety of DAPhen ligands are readily available,especially unsymmetrical ones,which give us a platform to systematically study the substituent effect on f-block elements extraction performance.The performance of unsymmetrical extractants is experimentally confirmed to falls between that of their corresponding symmetrical extractants by extracting UO_(2)^(2+) as the representative f-block element.This work provides a direct and versatile method to synthesize symmetrical and unsymmetrical DAPhen,which paves way for the investigations on their coordination properties with metal ions and other applications.展开更多
Text semantic extraction has been envisioned as a promising solution to improve the data transmission efficiency with the limited radio resources for the autonomous interactions among machines and things in the future...Text semantic extraction has been envisioned as a promising solution to improve the data transmission efficiency with the limited radio resources for the autonomous interactions among machines and things in the future sixth-generation(6G)wireless networks.In this paper,we propose a Chinese text semantic extraction model,namely T-Pointer,to improve the quality of semantic extraction by integrating the Transformer with the pointer-generator network.The proposed T-Pointer model consists of a semantic encoder and a semantic decoder.In the encoding stage,we use the multi-head attention mechanism of the Transformer to extract semantic features from the input Chinese text.In the decoding stage,we first use the Transformer to extract multi-level global text features.Then,we introduce the pointer-generator network model to directly copy the keyword information from the source text.The simulation results demonstrate that the T-Pointer model can improve the bilingual evaluation understudy(BLEU)and recalloriented understudy for gisting evaluation(ROUGE)by 14.69%and 14.87%on average in comparison with the state-of-the-art models,respectively.Also,we implement the T-Pointer model on a semantic communication system based on the universal software radio peripheral(USRP)platform.The result shows that the packet delay of semantic transmission can be reduced by 52.05%on average,compared to traditional information transmission.展开更多
This article presents a new synergistic extraction system composed of Cyanex 272(C272,bis(2,4,4-trimethylpentyl)phosphinic acid)and iso-octanol for Sc_(3+) separation.The proposed synergistic system possessed an Sc^(3...This article presents a new synergistic extraction system composed of Cyanex 272(C272,bis(2,4,4-trimethylpentyl)phosphinic acid)and iso-octanol for Sc_(3+) separation.The proposed synergistic system possessed an Sc^(3+) extraction efficiency of 93.5%and a back-extraction efficiency of 82.7%,with selectivity coefficients of β_(Sc/Fe)=459 and β_(Sc/Al)=4241,which are considerably higher as compared to the current extraction systems.The extraction mechanism was studied and interpreted.The enhanced extraction efficiency is attributed to the increased hydrophobicity of the ternary complex,whereas the back-extraction efficiency can be ascribed to the attenuated stability of the complex.C272 and C272–iso-octanol systems also possess considerable surface activity,which is beneficial for the phase separation in solvent extraction.Based on the solvent extraction results,a preliminary study was conducted on polymer inclusion membranes(PIMs)using the binary system for Sc^(3+) separation to avoid the formation of the third phase,achieving an optimal initial flux of PIM of 6.71×10^(−4)mol·m^(−2)·h^(−1).Our results provide valuable information on highly efficient Sc^(3+) separation,and the study on PIM extraction has shown a green alternative to solvent extraction.展开更多
Deep learning has made significant progress in the field of oriented object detection for remote sensing images.However,existing methods still face challenges when dealing with difficult tasks such as multi-scale targ...Deep learning has made significant progress in the field of oriented object detection for remote sensing images.However,existing methods still face challenges when dealing with difficult tasks such as multi-scale targets,complex backgrounds,and small objects in remote sensing.Maintaining model lightweight to address resource constraints in remote sensing scenarios while improving task completion for remote sensing tasks remains a research hotspot.Therefore,we propose an enhanced multi-scale feature extraction lightweight network EM-YOLO based on the YOLOv8s architecture,specifically optimized for the characteristics of large target scale variations,diverse orientations,and numerous small objects in remote sensing images.Our innovations lie in two main aspects:First,a dynamic snake convolution(DSC)is introduced into the backbone network to enhance the model’s feature extraction capability for oriented targets.Second,an innovative focusing-diffusion module is designed in the feature fusion neck to effectively integrate multi-scale feature information.Finally,we introduce Layer-Adaptive Sparsity for magnitude-based Pruning(LASP)method to perform lightweight network pruning to better complete tasks in resource-constrained scenarios.Experimental results on the lightweight platform Orin demonstrate that the proposed method significantly outperforms the original YOLOv8s model in oriented remote sensing object detection tasks,and achieves comparable or superior performance to state-of-the-art methods on three authoritative remote sensing datasets(DOTA v1.0,DOTA v1.5,and HRSC2016).展开更多
To ease the scarcity of lithium(Li)resource and cut down on environmental pollution,an efficient,selective,inexpensive and sustainable Li recycling process from waste batteries is needed,which is yet to be achieved.He...To ease the scarcity of lithium(Li)resource and cut down on environmental pollution,an efficient,selective,inexpensive and sustainable Li recycling process from waste batteries is needed,which is yet to be achieved.Here,we report a low-potential photoelectrochemical(PEC)system that selectively and efficiently extracts Li metals from multi-cation electrolytes under 1 sun illumination.Based on the difference of redox potential,we can get rid of the disturbance of other cations(i.e.,Fe,Co and Ni ions)by a bias-free PEC device to realize the extraction of high-purity Li metals on a coplanar Si-based photocathode-TiO_(2) photoanode tandem device at 2 V of applied bias(far less than the redox potentials of Li^(+)/Li).In such system,the extraction rate of Li metals(purity>99.5%)exceeds 1.35 g h^(-1)m^(-2)with 90%of Faradaic efficiency.Long-term experiments,different electrode/electrolyte tests,and various price assessments further demonstrate the stability,compatibility and economy of PEC extraction system,enabling a solar-driven pathway for the recycling of critical metal resources.展开更多
As a key low-carbon energy source,nuclear power plays a vital role in the global transition toward sustainable energy.Photocatalytic uranium extraction from seawater(UES)offers a promising solution to ensure long-term...As a key low-carbon energy source,nuclear power plays a vital role in the global transition toward sustainable energy.Photocatalytic uranium extraction from seawater(UES)offers a promising solution to ensure long-term uranium supply but is challenged by ultra-low uranium concentrations and ion interference.To overcome these issues,we design three diketopyrrolopyrrole-based covalent organic frameworks(COFs)via a synergisticπ-extended lock and carboxyl-functionalized anchor molecular engineering strategy.Among them,TPy-DPP-COF features a covalently lockedπ-conjugated structure that enhances planarity,optimizes energy alignment,and minimizes exciton binding energy,thereby promoting charge transfer and suppressing recombination.Concurrently,carboxyl groups enable uranyl-specific coordination and create local electric fields to facilitate charge separation.These features contribute to the outstanding performance of TPy-DPP-COF,which achieves a high uranium adsorption capacity of 16.33 mg g−1 in natural seawater under irradiation,with only 29.3%capacity loss after 10 cycles,surpassing industrial benchmarks.Density functional theory(DFT)calculations and experimental studies reveal a synergistic photocatalysis-adsorption pathway,with DPP units acting as active sites for uranium reduction.This work highlights a molecular design strategy for developing efficient COF-based photocatalysts for practical marine uranium recovery.展开更多
AIM:To investigate the long-term outcomes in acute primary angle closure(APAC)patients treated with lens extraction(LE)surgery and to identify risk factors for glaucomatous optic neuropathy(GON).METHODS:In this longit...AIM:To investigate the long-term outcomes in acute primary angle closure(APAC)patients treated with lens extraction(LE)surgery and to identify risk factors for glaucomatous optic neuropathy(GON).METHODS:In this longitudinal observational study,detailed medical histories of APAC patients and comprehensive ophthalmic examinations at final followup were collected.Logistic regression analysis was performed to identify predictors of blindness.Univariate and multivariate linear regression analyses were conducted to determine risk factors associated with visual outcomes.RESULTS:This study included 39 affected eyes of 31 subjects(26 females)with an average age of 74.1±8.0y.At 6.7±4.2y after APAC attack,2(5.7%)eyes had bestcorrected visual acuity(VA)worse than 3/60.Advanced glaucomatous visual field loss was observed in 15(39.5%)affected eyes and 5(25.0%)fellow eyes.Nine affected eyes(23.7%)had GON,and 11(28.9%)were blind.Six(15.4%)affected eyes and 2(9.1%)fellow eyes had suspicious progression.A significantly higher blindness rate in factory workers compared to office workers.Logistic regression identified that worse VA at attack(OR 10.568,95%CI 1.288-86.695;P=0.028)and worse early postoperative VA(OR 13.214,95%CI 1.157-150.881;P=0.038)were risk factors for blindness.Multivariate regression showed that longer duration of elevated intraocular pressure(P=0.004)and worse early postoperative VA(P=0.009)were associated with worse visual outcomes.CONCLUSION:Despite LE surgery,some APAC patients experience continued visual function deterioration.Lifelong monitoring is necessary.Target pressure and progression rates should be re-evaluated during follow-up.展开更多
Since Google introduced the concept of Knowledge Graphs(KGs)in 2012,their construction technologies have evolved into a comprehensive methodological framework encompassing knowledge acquisition,extraction,representati...Since Google introduced the concept of Knowledge Graphs(KGs)in 2012,their construction technologies have evolved into a comprehensive methodological framework encompassing knowledge acquisition,extraction,representation,modeling,fusion,computation,and storage.Within this framework,knowledge extraction,as the core component,directly determines KG quality.In military domains,traditional manual curation models face efficiency constraints due to data fragmentation,complex knowledge architectures,and confidentiality protocols.Meanwhile,crowdsourced ontology construction approaches from general domains prove non-transferable,while human-crafted ontologies struggle with generalization deficiencies.To address these challenges,this study proposes an OntologyAware LLM Methodology for Military Domain Knowledge Extraction(LLM-KE).This approach leverages the deep semantic comprehension capabilities of Large Language Models(LLMs)to simulate human experts’cognitive processes in crowdsourced ontology construction,enabling automated extraction of military textual knowledge.It concurrently enhances knowledge processing efficiency and improves KG completeness.Empirical analysis demonstrates that this method effectively resolves scalability and dynamic adaptation challenges in military KG construction,establishing a novel technological pathway for advancing military intelligence development.展开更多
As Satellite Frequency and Orbit(SFO)constitute scarce natural resources,constructing a Satellite Frequency and Orbit Knowledge Graph(SFO-KG)becomes crucial for optimizing their utilization.In the process of building ...As Satellite Frequency and Orbit(SFO)constitute scarce natural resources,constructing a Satellite Frequency and Orbit Knowledge Graph(SFO-KG)becomes crucial for optimizing their utilization.In the process of building the SFO-KG from Chinese unstructured data,extracting Chinese entity relations is the fundamental step.Although Relation Extraction(RE)methods in the English field have been extensively studied and developed earlier than their Chinese counterparts,their direct application to Chinese texts faces significant challenges due to linguistic distinctions such as unique grammar,pictographic characters,and prevalent polysemy.The absence of comprehensive reviews on Chinese RE research progress necessitates a systematic investigation.A thorough review of Chinese RE has been conducted from four methodological approaches:pipeline RE,joint entityrelation extraction,open domain RE,and multimodal RE techniques.In addition,we further analyze the essential research infrastructure,including specialized datasets,evaluation benchmarks,and competitions within Chinese RE research.Finally,the current research challenges and development trends in the field of Chinese RE were summarized and analyzed from the perspectives of ecological construction methods for datasets,open domain RE,N-ary RE,and RE based on large language models.This comprehensive review aims to facilitate SFO-KG construction and its practical applications in SFO resource management.展开更多
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
Solid phase extraction （SPE） is a widely used sample pretreatment method for separation, purification and enrichment, which has been established due to its significant advantages of time-saving, low consumption of s...Solid phase extraction （SPE） is a widely used sample pretreatment method for separation, purification and enrichment, which has been established due to its significant advantages of time-saving, low consumption of solvent, high enrichment factor, high accuracy, etc. In recent years, a variety of new SPE methods such as molecularly imprinted solid phase extraction （MISPE）, magnetic solid phase extraction （MSPE）, solid phase micro-extraction （SPME）, etc., which are superior to the conventional SPE, have been developed and been widely applied to food, drugs, and environmental monitoring. In this paper, the basic principles and methods of SPE and its new applications in different areas are reviewed.展开更多
Information extraction(IE)aims to automatically identify and extract information about specific interests from raw texts.Despite the abundance of solutions based on fine-tuning pretrained language models,IE in the con...Information extraction(IE)aims to automatically identify and extract information about specific interests from raw texts.Despite the abundance of solutions based on fine-tuning pretrained language models,IE in the context of fewshot and zero-shot scenarios remains highly challenging due to the scarcity of training data.Large language models(LLMs),on the other hand,can generalize well to unseen tasks with few-shot demonstrations or even zero-shot instructions and have demonstrated impressive ability for a wide range of natural language understanding or generation tasks.Nevertheless,it is unclear,whether such effectiveness can be replicated in the task of IE,where the target tasks involve specialized schema and quite abstractive entity or relation concepts.In this paper,we first examine the validity of LLMs in executing IE tasks with an established prompting strategy and further propose multiple types of augmented prompting methods,including the structured fundamental prompt(SFP),the structured interactive reasoning prompt(SIRP),and the voting-enabled structured interactive reasoning prompt(VESIRP).The experimental results demonstrate that while directly promotes inferior performance,the proposed augmented prompt methods significantly improve the extraction accuracy,achieving comparable or even better performance(e.g.,zero-shot FewNERD,FewNERD-INTRA)than state-of-theart methods that require large-scale training samples.This study represents a systematic exploration of employing instruction-following LLM for the task of IE.It not only establishes a performance benchmark for this novel paradigm but,more importantly,validates a practical technical pathway through the proposed prompt enhancement method,offering a viable solution for efficient IE in low-resource settings.展开更多
This study details a comprehensive approach focusing on the effective separation of light rare earth elements(REEs)via solvent extraction technique.A stock solution containing lanthanum,cerium,neodymium,praseodymium,a...This study details a comprehensive approach focusing on the effective separation of light rare earth elements(REEs)via solvent extraction technique.A stock solution containing lanthanum,cerium,neodymium,praseodymium,and samarium was prepared by dissolving their pure mixed oxide(reclaimed from spent Ni-MH batteries)in a diluted HCl solution.Key extractants,including bis(2,4,4-trimethylpentyl)phosphinic acid(Cyanex 272),Cyanex 572,trialkylphosphine oxide(Cyanex 923),and 2-ethylhexylphosphonic acid mono-2-ethylhexyl ester(PC 88A),along with tributyl phosphate(TBP)as a phase modifier,were utilized to form organic systems.The extraction behavior and separability of these systems at various pH levels as well as their extraction mechanisms were investigated.The results demonstrated a direct relationship between the extraction trend and the experimental pH value,with enhanced selectivity when TBP was added.Notably,Nd and Pr exhibited similar extraction behaviors,with minor deviations from Ce,making their separation difficult to achieve.Sm extraction followed a distinct trend,allowing for its separation from other elements at pH≤2.In contrast,La exhibited a low affinity for coordination with extractants when pH was≤3.5,facilitating the separation of other elements from La,which could then be isolated in the raffinate.Among the studied organic systems,combinations of Cyanex 572 and PC 88A with TBP demonstrated superior performance in element separation.Optimum separation factors were calculated withβ_(Ce/La)=12,βNd/La=87,β_(Pr/La)=127,andβ_(Sm/La)=3191 for the former,andβ_(Sm/Ce)=54,β_(Sm/Nd)=20,andβ_(Sm/Pr)=14 for the latter.These findings provide valuable insights for selecting extraction systems and designing experiments for the effective solvent extraction separation of light REEs from their mixture.展开更多
Simultaneous recovery of Ni and Co from Fe(Ⅲ)and AI is a critical challenge in hydrometallurgical processes.Recognized solvent extraction systems often struggle with selectivity and effective performance in mixed met...Simultaneous recovery of Ni and Co from Fe(Ⅲ)and AI is a critical challenge in hydrometallurgical processes.Recognized solvent extraction systems often struggle with selectivity and effective performance in mixed metal ion environments.Herein,a new synergistic solvent extraction(SSX)system comprised of a novel pyridine analog,N,N-bis(pyridin-2-ylmethyl)dodecan-1-amine(BPMDA),and dinonylnaphthalene sulfonic acid(DNNSA)with tributyl phosphate as phase modifier is introduced.The SSX system demonstrates high extraction performance achieving>90%for Ni and>97%for Co in a singlestage extraction process,with high selectivity.Under optimal conditions,the selectivity sequence is observed as Co^(2+)(>97%)>Ni^(2+)(>90%)>Mn^(2+)(<20%)>Fe^(3+)(<10%)>Mg^(2+)(<5%)>Al^(3+)(<2%)>Ca^(2+)(<1%).Spectroscopic analysis evidences the preferential binding of BPMDA with Ni and Co in the presence of DNNSA,concurrently achieving a significant reduction in the co-extraction of Fe(Ⅲ)and Al.The selective complexation of Ni and Co using the SSX system offers a highly efficient and selective approach for their extraction,with promising potential for applications in recovery-based processes.展开更多
Elemental doping of BiVO_(4) crystal lattices effectively enhances carrier separation,thereby facilitating efficient photoelectrochemical water splitting.However,the positive effect of elementally induced lattice dist...Elemental doping of BiVO_(4) crystal lattices effectively enhances carrier separation,thereby facilitating efficient photoelectrochemical water splitting.However,the positive effect of elementally induced lattice distortions on hole extraction has been neglected.Herein,the crystal lattice of BiVO_(4) is distorted by doping with an inexpensive Cs metal;then,CoFe_(2)O_(4) is used as an efficient hole-extraction layer to further modify the surface of the doped photoanode.Benefiting from the above design,the newly prepared CoFe_(2)O_(4)-Cs-BiVO_(4) photoanode achieved a photocurrent density of 5.66 mA cm^(–2) at 1.23 V vs.a reversible hydrogen electrode,indicating a 3.9-fold improvement in photocurrent density.Detailed physicochemical characterization and density functional theory calculations showed that the lattice distortion induced by Cs doping promoted the directional migration of BiVO_(4) bulk-phase holes to the CoFe_(2)O_(4) layer.Additionally,the coupled CoFe_(2)O_(4) can be used as a hole extraction layer to further enhance the interfacial migration of carriers.The synergistic effect of the two effectively promotes the directional migration of photogenerated carriers from the BiVO_(4) bulk phase to the active sites of the oxygen evolution reaction,thereby effectively inhibiting carrier recombination.This study revealed the positive effect of the dual-hole extraction strategy on solar energy conversion,thereby opening new avenues for the rational design of photoanodes.展开更多
[Objective] The aim of this study was to find a better method to exactly quantify the residual polycyclic aromatic hydrocarbons（PAHs）in the long-term contaminated soil in the field so as to provide basis for the rem...[Objective] The aim of this study was to find a better method to exactly quantify the residual polycyclic aromatic hydrocarbons（PAHs）in the long-term contaminated soil in the field so as to provide basis for the remediation for PAHs contaminated soil.[Method]The comparisons of soxhlet extraction,ultrasonic extraction and shaking extraction were studied in the agricultural soil irrigated with oil sewage over a long period of time.[Result]The total PAHs extracted by soxhlet extraction were the highest（6 873.7 μg/kg）,followed by shaking extraction（6 698.8 μg/kg）and ultrasonic extraction（5 737.6 μg/kg）.Among these methods,the highest extracted 4 and 6 rings PAHs were in the soxhlet extraction,the highest extracted 2 and 5 rings PAHs were in the shaking extraction,and the highest extracted 3 rings PAHs were in the ultrasonic extraction.[Conclusion]This study had provided basis for the selection of the assessment method of residual PAHs in the field soil.展开更多
Using experimental data from a number of pulsed disc and doughnut solvent extraction columns, a unified correla- tion for the prediction of dispersed phase holdup that considers the effects of mass transfer is present...Using experimental data from a number of pulsed disc and doughnut solvent extraction columns, a unified correla- tion for the prediction of dispersed phase holdup that considers the effects of mass transfer is presented. Pulsed disc and doughnut solvent extraction columns （PDDC） have been used for a range of important applications such as ura- nium extraction and nuclear fuel recycling. Although the dispersed phase holdup in a PDDC has been presented by some researchers, there is still the need to develop a robust correlation that can predict the experimental dispersed phase holdup over a range of operating conditions including the effects of mass transfer direction. In this study, dis- persed phase holdup data from different literature sources for a PDDC were used to refit constants for the correlation presented by Kumar and Hartland lind. Eng. Chem. Res.,27 （1988）,131-138] which did not consider the effect of col- umn geometry. In order to incorporate the characteristic length of the PDDC （i.e. the plate spacing）, the unified cor- relation for holdup proposed by Kumar and Hartland based on data from eight different types of columns [Ind. Eng. Chem. Res.,34 （1995） 3925-3940] was refitted to the PDDC data. New constants have been presented for each hold- up correlation for a PDDC based on regression analysis using published holdup data from PDDCs that cover a range of onerating conditions and nhwical nronerties and consider the direction of mass transfer.展开更多
In the international shipping industry, digital intelligence transformation has become essential, with both governments and enterprises actively working to integrate diverse datasets. The domain of maritime and shippi...In the international shipping industry, digital intelligence transformation has become essential, with both governments and enterprises actively working to integrate diverse datasets. The domain of maritime and shipping is characterized by a vast array of document types, filled with complex, large-scale, and often chaotic knowledge and relationships. Effectively managing these documents is crucial for developing a Large Language Model (LLM) in the maritime domain, enabling practitioners to access and leverage valuable information. A Knowledge Graph (KG) offers a state-of-the-art solution for enhancing knowledge retrieval, providing more accurate responses and enabling context-aware reasoning. This paper presents a framework for utilizing maritime and shipping documents to construct a knowledge graph using GraphRAG, a hybrid tool combining graph-based retrieval and generation capabilities. The extraction of entities and relationships from these documents and the KG construction process are detailed. Furthermore, the KG is integrated with an LLM to develop a Q&A system, demonstrating that the system significantly improves answer accuracy compared to traditional LLMs. Additionally, the KG construction process is up to 50% faster than conventional LLM-based approaches, underscoring the efficiency of our method. This study provides a promising approach to digital intelligence in shipping, advancing knowledge accessibility and decision-making.展开更多
文摘Standard bacterial suspensions play a crucial role in microbiological diagnosis.Traditional prepar-ation methods,which rely heavily on manual operations,face challenges such as poor reproducibility,low ef-ficiency,and biosafety concerns.In this study,we propose a high-precision automated colony extraction and separation system that combines large-field imaging and artificial intelligence(AI)to facilitate intelligent screening and localization of colonies.Firstly,a large-field imaging system was developed to capture high-resolution images of 90 mm Petri dishes,achieving a physical resolution of 13.2μm and an imaging speed of 13 frames per second.Subsequently,AI technology was employed for the automatic recognition and localiza-tion of colonies,enabling the selection of target colonies with diameters ranging from 1.9 to 2.3 mm.Next,a three-axis motion control platform was designed,accompanied by a path planning algorithm for the efficient extraction of colonies.An electronic pipette was employed for accurate colony collection.Additionally,a bacterial suspension concentration measurement module was developed,incorporating a 650 nm laser diode as the light source,achieving a measurement accuracy of 0.01 McFarland concentration(MCF).Finally,the system’s performance was validated through the preparation of an Esckerichia coli(E.coli)suspension.After 17 hours of cultivation,E.coli was extracted four times,achieving the target concentration set by the system.This work is expected to enable rapid and accurate microbial sample preparation,significantly reducing de-tection cycles and alleviating the workload of healthcare personnel.
基金supported by the National Natural Science Foundation of China(No.52403035)the Shanghai Sailing Program(23YF1400300)+1 种基金the Fundamental Research Funds for the Central Universities(2232023D-05)the Weiqiao Teaching and Research Innovation Program.
文摘The lack of macro-continuity and mechanical strength of covalent organic frameworks(COFs)has significantly limited their practical applications.Here,we propose an“alcohol-triggered defect cleavage”strategy to precisely regulate the growth and stacking of COF grains through a moderate reversed Schiff base reaction,realizing the direct synthesis of COF nanofibers(CNFs)with high aspect ratio(L/D=103.05)and long length(>20μm).An individual CNF exhibits a biomimetic scale-like architecture,achieving superior flexibility and fatigue resistance under dynamic bending via a multiscale stress dissipation mechanism.Taking advantages of these structural features,we engineer CNF aerogels(CNF-As)with programmable porous structures(e.g.,honeycomb,lamellar,isotropic)via directional ice-template methodology.CNF-As demonstrate 100%COF content,high specific surface area(396.15 m^(2)g^(-1))and superelasticity(~0%elastic deformation after 500 compression cycles at 50%strain),outperforming most COF-based counterparts.Compared with the conventional COF aerogels,the unique structural features of CNF-A enable it to perform outstandingly in uranium extraction,with an 11.72-fold increment in adsorption capacity(920.12 mg g^(-1))and adsorption rate(89.9%),and a 2.48-fold improvement in selectivity(U/V=2.31).This study provides a direct strategy for the development of next-generation COF materials with outstanding functionality and structural robustness.
基金financial support from the National Natural Science Foundation of China (Nos.22476178,U2067213)Natural Science Foundation of Zhejiang Province (No.LRG25B060002)。
文摘As an important class of phenanthroline derivatives containing soft N and hard O donor atoms,the laborious syntheses of unsymmetrical 1,10-phenanthroline-derived diamide ligands(DAPhen) have hindered its extensive study.In this work,we first report a convenient synthetic method for the construction of DAPhen using Friedländer reaction by two facile steps(vs.previous 12 steps).A variety of DAPhen ligands are readily available,especially unsymmetrical ones,which give us a platform to systematically study the substituent effect on f-block elements extraction performance.The performance of unsymmetrical extractants is experimentally confirmed to falls between that of their corresponding symmetrical extractants by extracting UO_(2)^(2+) as the representative f-block element.This work provides a direct and versatile method to synthesize symmetrical and unsymmetrical DAPhen,which paves way for the investigations on their coordination properties with metal ions and other applications.
基金National Natural Science Foundation of China under Grants 62122069,62071431,62072490,62301490Science and Technology Development Fund of Macao,Macao,China under Grant 0158/2022/A+2 种基金Guangdong Basic and Applied Basic Research Foundation(2022A1515011287)MYRG2020-00107-IOTSCFDCT SKL-IOTSC(UM)-2021-2023。
文摘Text semantic extraction has been envisioned as a promising solution to improve the data transmission efficiency with the limited radio resources for the autonomous interactions among machines and things in the future sixth-generation(6G)wireless networks.In this paper,we propose a Chinese text semantic extraction model,namely T-Pointer,to improve the quality of semantic extraction by integrating the Transformer with the pointer-generator network.The proposed T-Pointer model consists of a semantic encoder and a semantic decoder.In the encoding stage,we use the multi-head attention mechanism of the Transformer to extract semantic features from the input Chinese text.In the decoding stage,we first use the Transformer to extract multi-level global text features.Then,we introduce the pointer-generator network model to directly copy the keyword information from the source text.The simulation results demonstrate that the T-Pointer model can improve the bilingual evaluation understudy(BLEU)and recalloriented understudy for gisting evaluation(ROUGE)by 14.69%and 14.87%on average in comparison with the state-of-the-art models,respectively.Also,we implement the T-Pointer model on a semantic communication system based on the universal software radio peripheral(USRP)platform.The result shows that the packet delay of semantic transmission can be reduced by 52.05%on average,compared to traditional information transmission.
基金support from the National Natural Science Foundation of China Regional Innovation and Development Joint Fund(U24A20557)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDC0230403)+3 种基金the National Natural Science Foundation of China(22378393,22208356)“Hundred Talents Program”of the Chinese Academy of Sciencesthe Chinese Academy of Sciences stably supports the youth team plan in the field of basic research(YSBR 038)Key Research&Development projects in Qinghai Province(2023-HZ-805).
文摘This article presents a new synergistic extraction system composed of Cyanex 272(C272,bis(2,4,4-trimethylpentyl)phosphinic acid)and iso-octanol for Sc_(3+) separation.The proposed synergistic system possessed an Sc^(3+) extraction efficiency of 93.5%and a back-extraction efficiency of 82.7%,with selectivity coefficients of β_(Sc/Fe)=459 and β_(Sc/Al)=4241,which are considerably higher as compared to the current extraction systems.The extraction mechanism was studied and interpreted.The enhanced extraction efficiency is attributed to the increased hydrophobicity of the ternary complex,whereas the back-extraction efficiency can be ascribed to the attenuated stability of the complex.C272 and C272–iso-octanol systems also possess considerable surface activity,which is beneficial for the phase separation in solvent extraction.Based on the solvent extraction results,a preliminary study was conducted on polymer inclusion membranes(PIMs)using the binary system for Sc^(3+) separation to avoid the formation of the third phase,achieving an optimal initial flux of PIM of 6.71×10^(−4)mol·m^(−2)·h^(−1).Our results provide valuable information on highly efficient Sc^(3+) separation,and the study on PIM extraction has shown a green alternative to solvent extraction.
基金funded by the Hainan Province Science and Technology Special Fund under Grant ZDYF2024GXJS292.
文摘Deep learning has made significant progress in the field of oriented object detection for remote sensing images.However,existing methods still face challenges when dealing with difficult tasks such as multi-scale targets,complex backgrounds,and small objects in remote sensing.Maintaining model lightweight to address resource constraints in remote sensing scenarios while improving task completion for remote sensing tasks remains a research hotspot.Therefore,we propose an enhanced multi-scale feature extraction lightweight network EM-YOLO based on the YOLOv8s architecture,specifically optimized for the characteristics of large target scale variations,diverse orientations,and numerous small objects in remote sensing images.Our innovations lie in two main aspects:First,a dynamic snake convolution(DSC)is introduced into the backbone network to enhance the model’s feature extraction capability for oriented targets.Second,an innovative focusing-diffusion module is designed in the feature fusion neck to effectively integrate multi-scale feature information.Finally,we introduce Layer-Adaptive Sparsity for magnitude-based Pruning(LASP)method to perform lightweight network pruning to better complete tasks in resource-constrained scenarios.Experimental results on the lightweight platform Orin demonstrate that the proposed method significantly outperforms the original YOLOv8s model in oriented remote sensing object detection tasks,and achieves comparable or superior performance to state-of-the-art methods on three authoritative remote sensing datasets(DOTA v1.0,DOTA v1.5,and HRSC2016).
基金the National Natural Science Foundation of China(22479047,22409058)the Outstanding Youth Scientist Foundation of Hunan Province(2022JJ10023)the Provincial Natural Science Foundation of Guangdong(2023A1515011745)for financial support of this research。
文摘To ease the scarcity of lithium(Li)resource and cut down on environmental pollution,an efficient,selective,inexpensive and sustainable Li recycling process from waste batteries is needed,which is yet to be achieved.Here,we report a low-potential photoelectrochemical(PEC)system that selectively and efficiently extracts Li metals from multi-cation electrolytes under 1 sun illumination.Based on the difference of redox potential,we can get rid of the disturbance of other cations(i.e.,Fe,Co and Ni ions)by a bias-free PEC device to realize the extraction of high-purity Li metals on a coplanar Si-based photocathode-TiO_(2) photoanode tandem device at 2 V of applied bias(far less than the redox potentials of Li^(+)/Li).In such system,the extraction rate of Li metals(purity>99.5%)exceeds 1.35 g h^(-1)m^(-2)with 90%of Faradaic efficiency.Long-term experiments,different electrode/electrolyte tests,and various price assessments further demonstrate the stability,compatibility and economy of PEC extraction system,enabling a solar-driven pathway for the recycling of critical metal resources.
基金the Young Elite Scientists Sponsorship Program by JXAST(2024QT11)the National Natural Science Foundation of China(22465001,22309003)the Jiangxi Provincial Natural Science Foundation(20232BAB203042,20242BAB22002).
文摘As a key low-carbon energy source,nuclear power plays a vital role in the global transition toward sustainable energy.Photocatalytic uranium extraction from seawater(UES)offers a promising solution to ensure long-term uranium supply but is challenged by ultra-low uranium concentrations and ion interference.To overcome these issues,we design three diketopyrrolopyrrole-based covalent organic frameworks(COFs)via a synergisticπ-extended lock and carboxyl-functionalized anchor molecular engineering strategy.Among them,TPy-DPP-COF features a covalently lockedπ-conjugated structure that enhances planarity,optimizes energy alignment,and minimizes exciton binding energy,thereby promoting charge transfer and suppressing recombination.Concurrently,carboxyl groups enable uranyl-specific coordination and create local electric fields to facilitate charge separation.These features contribute to the outstanding performance of TPy-DPP-COF,which achieves a high uranium adsorption capacity of 16.33 mg g−1 in natural seawater under irradiation,with only 29.3%capacity loss after 10 cycles,surpassing industrial benchmarks.Density functional theory(DFT)calculations and experimental studies reveal a synergistic photocatalysis-adsorption pathway,with DPP units acting as active sites for uranium reduction.This work highlights a molecular design strategy for developing efficient COF-based photocatalysts for practical marine uranium recovery.
文摘AIM:To investigate the long-term outcomes in acute primary angle closure(APAC)patients treated with lens extraction(LE)surgery and to identify risk factors for glaucomatous optic neuropathy(GON).METHODS:In this longitudinal observational study,detailed medical histories of APAC patients and comprehensive ophthalmic examinations at final followup were collected.Logistic regression analysis was performed to identify predictors of blindness.Univariate and multivariate linear regression analyses were conducted to determine risk factors associated with visual outcomes.RESULTS:This study included 39 affected eyes of 31 subjects(26 females)with an average age of 74.1±8.0y.At 6.7±4.2y after APAC attack,2(5.7%)eyes had bestcorrected visual acuity(VA)worse than 3/60.Advanced glaucomatous visual field loss was observed in 15(39.5%)affected eyes and 5(25.0%)fellow eyes.Nine affected eyes(23.7%)had GON,and 11(28.9%)were blind.Six(15.4%)affected eyes and 2(9.1%)fellow eyes had suspicious progression.A significantly higher blindness rate in factory workers compared to office workers.Logistic regression identified that worse VA at attack(OR 10.568,95%CI 1.288-86.695;P=0.028)and worse early postoperative VA(OR 13.214,95%CI 1.157-150.881;P=0.038)were risk factors for blindness.Multivariate regression showed that longer duration of elevated intraocular pressure(P=0.004)and worse early postoperative VA(P=0.009)were associated with worse visual outcomes.CONCLUSION:Despite LE surgery,some APAC patients experience continued visual function deterioration.Lifelong monitoring is necessary.Target pressure and progression rates should be re-evaluated during follow-up.
文摘Since Google introduced the concept of Knowledge Graphs(KGs)in 2012,their construction technologies have evolved into a comprehensive methodological framework encompassing knowledge acquisition,extraction,representation,modeling,fusion,computation,and storage.Within this framework,knowledge extraction,as the core component,directly determines KG quality.In military domains,traditional manual curation models face efficiency constraints due to data fragmentation,complex knowledge architectures,and confidentiality protocols.Meanwhile,crowdsourced ontology construction approaches from general domains prove non-transferable,while human-crafted ontologies struggle with generalization deficiencies.To address these challenges,this study proposes an OntologyAware LLM Methodology for Military Domain Knowledge Extraction(LLM-KE).This approach leverages the deep semantic comprehension capabilities of Large Language Models(LLMs)to simulate human experts’cognitive processes in crowdsourced ontology construction,enabling automated extraction of military textual knowledge.It concurrently enhances knowledge processing efficiency and improves KG completeness.Empirical analysis demonstrates that this method effectively resolves scalability and dynamic adaptation challenges in military KG construction,establishing a novel technological pathway for advancing military intelligence development.
文摘As Satellite Frequency and Orbit(SFO)constitute scarce natural resources,constructing a Satellite Frequency and Orbit Knowledge Graph(SFO-KG)becomes crucial for optimizing their utilization.In the process of building the SFO-KG from Chinese unstructured data,extracting Chinese entity relations is the fundamental step.Although Relation Extraction(RE)methods in the English field have been extensively studied and developed earlier than their Chinese counterparts,their direct application to Chinese texts faces significant challenges due to linguistic distinctions such as unique grammar,pictographic characters,and prevalent polysemy.The absence of comprehensive reviews on Chinese RE research progress necessitates a systematic investigation.A thorough review of Chinese RE has been conducted from four methodological approaches:pipeline RE,joint entityrelation extraction,open domain RE,and multimodal RE techniques.In addition,we further analyze the essential research infrastructure,including specialized datasets,evaluation benchmarks,and competitions within Chinese RE research.Finally,the current research challenges and development trends in the field of Chinese RE were summarized and analyzed from the perspectives of ecological construction methods for datasets,open domain RE,N-ary RE,and RE based on large language models.This comprehensive review aims to facilitate SFO-KG construction and its practical applications in SFO resource management.
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 the Key Laboratory for Rare Disease of Shandong Province
文摘Solid phase extraction （SPE） is a widely used sample pretreatment method for separation, purification and enrichment, which has been established due to its significant advantages of time-saving, low consumption of solvent, high enrichment factor, high accuracy, etc. In recent years, a variety of new SPE methods such as molecularly imprinted solid phase extraction （MISPE）, magnetic solid phase extraction （MSPE）, solid phase micro-extraction （SPME）, etc., which are superior to the conventional SPE, have been developed and been widely applied to food, drugs, and environmental monitoring. In this paper, the basic principles and methods of SPE and its new applications in different areas are reviewed.
基金supported by the National Natural Science Foundation of China(62222212).
文摘Information extraction(IE)aims to automatically identify and extract information about specific interests from raw texts.Despite the abundance of solutions based on fine-tuning pretrained language models,IE in the context of fewshot and zero-shot scenarios remains highly challenging due to the scarcity of training data.Large language models(LLMs),on the other hand,can generalize well to unseen tasks with few-shot demonstrations or even zero-shot instructions and have demonstrated impressive ability for a wide range of natural language understanding or generation tasks.Nevertheless,it is unclear,whether such effectiveness can be replicated in the task of IE,where the target tasks involve specialized schema and quite abstractive entity or relation concepts.In this paper,we first examine the validity of LLMs in executing IE tasks with an established prompting strategy and further propose multiple types of augmented prompting methods,including the structured fundamental prompt(SFP),the structured interactive reasoning prompt(SIRP),and the voting-enabled structured interactive reasoning prompt(VESIRP).The experimental results demonstrate that while directly promotes inferior performance,the proposed augmented prompt methods significantly improve the extraction accuracy,achieving comparable or even better performance(e.g.,zero-shot FewNERD,FewNERD-INTRA)than state-of-theart methods that require large-scale training samples.This study represents a systematic exploration of employing instruction-following LLM for the task of IE.It not only establishes a performance benchmark for this novel paradigm but,more importantly,validates a practical technical pathway through the proposed prompt enhancement method,offering a viable solution for efficient IE in low-resource settings.
基金support from the Australian Research Council’s Industrial Transformation Research Hub funding scheme(project IH190100009).
文摘This study details a comprehensive approach focusing on the effective separation of light rare earth elements(REEs)via solvent extraction technique.A stock solution containing lanthanum,cerium,neodymium,praseodymium,and samarium was prepared by dissolving their pure mixed oxide(reclaimed from spent Ni-MH batteries)in a diluted HCl solution.Key extractants,including bis(2,4,4-trimethylpentyl)phosphinic acid(Cyanex 272),Cyanex 572,trialkylphosphine oxide(Cyanex 923),and 2-ethylhexylphosphonic acid mono-2-ethylhexyl ester(PC 88A),along with tributyl phosphate(TBP)as a phase modifier,were utilized to form organic systems.The extraction behavior and separability of these systems at various pH levels as well as their extraction mechanisms were investigated.The results demonstrated a direct relationship between the extraction trend and the experimental pH value,with enhanced selectivity when TBP was added.Notably,Nd and Pr exhibited similar extraction behaviors,with minor deviations from Ce,making their separation difficult to achieve.Sm extraction followed a distinct trend,allowing for its separation from other elements at pH≤2.In contrast,La exhibited a low affinity for coordination with extractants when pH was≤3.5,facilitating the separation of other elements from La,which could then be isolated in the raffinate.Among the studied organic systems,combinations of Cyanex 572 and PC 88A with TBP demonstrated superior performance in element separation.Optimum separation factors were calculated withβ_(Ce/La)=12,βNd/La=87,β_(Pr/La)=127,andβ_(Sm/La)=3191 for the former,andβ_(Sm/Ce)=54,β_(Sm/Nd)=20,andβ_(Sm/Pr)=14 for the latter.These findings provide valuable insights for selecting extraction systems and designing experiments for the effective solvent extraction separation of light REEs from their mixture.
基金supported by the National Natural Science Foundation of China(22278407,22001147,21922814,22138012,22178349)CAS Project for Young Scientists in Basic Research(YSBR-038)+2 种基金the Ministry of Science and Technology of China(2021YFC2901500)Excellent Member in Youth Innovation Promotion Association,Chinese Academy of Sciences(Y202014)Shandong Energy Institute(SEI U202306).
文摘Simultaneous recovery of Ni and Co from Fe(Ⅲ)and AI is a critical challenge in hydrometallurgical processes.Recognized solvent extraction systems often struggle with selectivity and effective performance in mixed metal ion environments.Herein,a new synergistic solvent extraction(SSX)system comprised of a novel pyridine analog,N,N-bis(pyridin-2-ylmethyl)dodecan-1-amine(BPMDA),and dinonylnaphthalene sulfonic acid(DNNSA)with tributyl phosphate as phase modifier is introduced.The SSX system demonstrates high extraction performance achieving>90%for Ni and>97%for Co in a singlestage extraction process,with high selectivity.Under optimal conditions,the selectivity sequence is observed as Co^(2+)(>97%)>Ni^(2+)(>90%)>Mn^(2+)(<20%)>Fe^(3+)(<10%)>Mg^(2+)(<5%)>Al^(3+)(<2%)>Ca^(2+)(<1%).Spectroscopic analysis evidences the preferential binding of BPMDA with Ni and Co in the presence of DNNSA,concurrently achieving a significant reduction in the co-extraction of Fe(Ⅲ)and Al.The selective complexation of Ni and Co using the SSX system offers a highly efficient and selective approach for their extraction,with promising potential for applications in recovery-based processes.
文摘Elemental doping of BiVO_(4) crystal lattices effectively enhances carrier separation,thereby facilitating efficient photoelectrochemical water splitting.However,the positive effect of elementally induced lattice distortions on hole extraction has been neglected.Herein,the crystal lattice of BiVO_(4) is distorted by doping with an inexpensive Cs metal;then,CoFe_(2)O_(4) is used as an efficient hole-extraction layer to further modify the surface of the doped photoanode.Benefiting from the above design,the newly prepared CoFe_(2)O_(4)-Cs-BiVO_(4) photoanode achieved a photocurrent density of 5.66 mA cm^(–2) at 1.23 V vs.a reversible hydrogen electrode,indicating a 3.9-fold improvement in photocurrent density.Detailed physicochemical characterization and density functional theory calculations showed that the lattice distortion induced by Cs doping promoted the directional migration of BiVO_(4) bulk-phase holes to the CoFe_(2)O_(4) layer.Additionally,the coupled CoFe_(2)O_(4) can be used as a hole extraction layer to further enhance the interfacial migration of carriers.The synergistic effect of the two effectively promotes the directional migration of photogenerated carriers from the BiVO_(4) bulk phase to the active sites of the oxygen evolution reaction,thereby effectively inhibiting carrier recombination.This study revealed the positive effect of the dual-hole extraction strategy on solar energy conversion,thereby opening new avenues for the rational design of photoanodes.
基金Supported by Important Direction Project of Knowledge Innovation Program in Chinese Academy of Science(KZCX2-YW-446)~~
文摘[Objective] The aim of this study was to find a better method to exactly quantify the residual polycyclic aromatic hydrocarbons（PAHs）in the long-term contaminated soil in the field so as to provide basis for the remediation for PAHs contaminated soil.[Method]The comparisons of soxhlet extraction,ultrasonic extraction and shaking extraction were studied in the agricultural soil irrigated with oil sewage over a long period of time.[Result]The total PAHs extracted by soxhlet extraction were the highest（6 873.7 μg/kg）,followed by shaking extraction（6 698.8 μg/kg）and ultrasonic extraction（5 737.6 μg/kg）.Among these methods,the highest extracted 4 and 6 rings PAHs were in the soxhlet extraction,the highest extracted 2 and 5 rings PAHs were in the shaking extraction,and the highest extracted 3 rings PAHs were in the ultrasonic extraction.[Conclusion]This study had provided basis for the selection of the assessment method of residual PAHs in the field soil.
文摘Using experimental data from a number of pulsed disc and doughnut solvent extraction columns, a unified correla- tion for the prediction of dispersed phase holdup that considers the effects of mass transfer is presented. Pulsed disc and doughnut solvent extraction columns （PDDC） have been used for a range of important applications such as ura- nium extraction and nuclear fuel recycling. Although the dispersed phase holdup in a PDDC has been presented by some researchers, there is still the need to develop a robust correlation that can predict the experimental dispersed phase holdup over a range of operating conditions including the effects of mass transfer direction. In this study, dis- persed phase holdup data from different literature sources for a PDDC were used to refit constants for the correlation presented by Kumar and Hartland lind. Eng. Chem. Res.,27 （1988）,131-138] which did not consider the effect of col- umn geometry. In order to incorporate the characteristic length of the PDDC （i.e. the plate spacing）, the unified cor- relation for holdup proposed by Kumar and Hartland based on data from eight different types of columns [Ind. Eng. Chem. Res.,34 （1995） 3925-3940] was refitted to the PDDC data. New constants have been presented for each hold- up correlation for a PDDC based on regression analysis using published holdup data from PDDCs that cover a range of onerating conditions and nhwical nronerties and consider the direction of mass transfer.
文摘In the international shipping industry, digital intelligence transformation has become essential, with both governments and enterprises actively working to integrate diverse datasets. The domain of maritime and shipping is characterized by a vast array of document types, filled with complex, large-scale, and often chaotic knowledge and relationships. Effectively managing these documents is crucial for developing a Large Language Model (LLM) in the maritime domain, enabling practitioners to access and leverage valuable information. A Knowledge Graph (KG) offers a state-of-the-art solution for enhancing knowledge retrieval, providing more accurate responses and enabling context-aware reasoning. This paper presents a framework for utilizing maritime and shipping documents to construct a knowledge graph using GraphRAG, a hybrid tool combining graph-based retrieval and generation capabilities. The extraction of entities and relationships from these documents and the KG construction process are detailed. Furthermore, the KG is integrated with an LLM to develop a Q&A system, demonstrating that the system significantly improves answer accuracy compared to traditional LLMs. Additionally, the KG construction process is up to 50% faster than conventional LLM-based approaches, underscoring the efficiency of our method. This study provides a promising approach to digital intelligence in shipping, advancing knowledge accessibility and decision-making.
