Among various architectures of polymers,end-group-free rings have attracted growing interests due to their distinct physicochemical performances over the linear counterparts which are exemplified by reduced hydrodynam...Among various architectures of polymers,end-group-free rings have attracted growing interests due to their distinct physicochemical performances over the linear counterparts which are exemplified by reduced hydrodynamic size and slower degradation.It is key to develop facile methods to large-scale synthesis of polymer rings with tunable compositions and microstructures.Recent progresses in large-scale synthesis of polymer rings against single-chain dynamic nanoparticles,and the example applications in synchronous enhancing toughness and strength of polymer nanocomposites are summarized.Once there is the breakthrough in rational design and effective large-scale synthesis of polymer rings and their functional derivatives,a family of cyclic functional hybrids would be available,thus providing a new paradigm in developing polymer science and engineering.展开更多
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
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
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
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
This article introduces the concept of load aggregation,which involves a comprehensive analysis of loads to acquire their external characteristics for the purpose of modeling and analyzing power systems.The online ide...This article introduces the concept of load aggregation,which involves a comprehensive analysis of loads to acquire their external characteristics for the purpose of modeling and analyzing power systems.The online identification method is a computer-involved approach for data collection,processing,and system identification,commonly used for adaptive control and prediction.This paper proposes a method for dynamically aggregating large-scale adjustable loads to support high proportions of new energy integration,aiming to study the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction methods.The experiment selected 300 central air conditioners as the research subject and analyzed their regulation characteristics,economic efficiency,and comfort.The experimental results show that as the adjustment time of the air conditioner increases from 5 minutes to 35 minutes,the stable adjustment quantity during the adjustment period decreases from 28.46 to 3.57,indicating that air conditioning loads can be controlled over a long period and have better adjustment effects in the short term.Overall,the experimental results of this paper demonstrate that analyzing the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction algorithms is effective.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
1.Introduction Climate change mitigation pathways aimed at limiting global anthropogenic carbon dioxide(CO_(2))emissions while striving to constrain the global temperature increase to below 2℃—as outlined by the Int...1.Introduction Climate change mitigation pathways aimed at limiting global anthropogenic carbon dioxide(CO_(2))emissions while striving to constrain the global temperature increase to below 2℃—as outlined by the Intergovernmental Panel on Climate Change(IPCC)—consistently predict the widespread implementation of CO_(2)geological storage on a global scale.展开更多
Solvent extraction is the main method used to separate and purify rare earth elements.In the process of rare earths extraction,emulsification often generated due to the instability of the aqueous and organic phases or...Solvent extraction is the main method used to separate and purify rare earth elements.In the process of rare earths extraction,emulsification often generated due to the instability of the aqueous and organic phases or improper operating conditions.Once emulsification occurs,it would not only lead to low rare earths recovery efficiency,small product quantities,high production costs and the losing of extractant and rare earth resources,but also result in serious environmental pollution.Therefore,it is very important to study the micro-mechanisms of emulsification and establish new methods to prevent emulsification at the source.In this paper,possible factors resulting in emulsification,such as the compositions and properties of the organic and aqueous phases,the operating conditions of the rare earths extraction are reviewed.The micro-mechanisms of emulsification are summarized basing on the microscopic structures in the bulk phase,aggregations of the extractants at the organic-aqueous interface,spectral characterizations and computational simulations.On this basis,new formation mechanisms are proposed for emulsification.Preliminary explorations are employed to verify the correctness of these new viewpoints.Finally,future directions for studies of the emulsification micro-mechanism are proposed.This study provides a theoretical basis for further understanding the micro-mechanisms of interfacial instability resulting in emulsification in the process of rare earths extraction.展开更多
The recent upsurge in metro construction emphasizes the necessity of understanding the mechanical performance of metro shield tunnel subjected to the influence of ground fissures.In this study,a largescale experiment,...The recent upsurge in metro construction emphasizes the necessity of understanding the mechanical performance of metro shield tunnel subjected to the influence of ground fissures.In this study,a largescale experiment,in combination with numerical simulation,was conducted to investigate the influence of ground fissures on a metro shield tunnel.The results indicate that the lining contact pressure at the vault increases in the hanging wall while decreases in the footwall,resulting in a two-dimensional stress state of vertical shear and axial tension-compression,and simultaneous vertical dislocation and axial tilt for the segments around the ground fissure.In addition,the damage to curved bolts includes tensile yield,flexural yield,and shear twist,leading to obvious concrete lining damage,particularly at the vault,arch bottom,and hance,indicating that the joints in these positions are weak areas.The shield tunnel orthogonal to the ground fissure ultimately experiences shear failure,suggesting that the maximum actual dislocation of ground fissure that the structure can withstand is approximately 20 cm,and five segment rings in the hanging wall and six segment rings in the footwall also need to be reinforced.This study could provide a reference for metro design in ground fissure sites.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
Based on the analysis of typical lacustrine shale oil zones in China and their geological characteristics,this study elucidates the fundamental differences between the enrichment patterns of shale oil sweet spots and ...Based on the analysis of typical lacustrine shale oil zones in China and their geological characteristics,this study elucidates the fundamental differences between the enrichment patterns of shale oil sweet spots and conventional oil and gas.The key parameters and evaluation methods for assessing the large-scale production potential of lacustrine shale oil are proposed.The results show that shale oil is a petroleum resource that exists in organic-rich shale formations,in other words,it is preserved in its source bed,following a different process of generation-accumulation-enrichment from conventional oil and gas.Thus,the concept of“reservoir”seems to be inapplicable to shale oil.In China,lacustrine shale oil is distributed widely,but the geological characteristics and sweet spots enrichment patterns of shale oil vary significantly in lacustrine basins where the water environment and the tectonic evolution and diagenetic transformation frameworks are distinct.The core of the evaluation of lacustrine shale oil is“sweet spot volume”.The key factors for evaluating the large-scale production of continental shale oil are the oil storage capacity,oil-bearing capacity and oil producing capacity.The key parameters for evaluating these capacities are total porosity,oil content,and free oil content,respectively.It is recommended to determine the total porosity of shale by combining helium porosity measurement with nuclear magnetic resonance(NMR)method,the oil content of key layers by using organic solvent extraction,NMR method and high pressure mercury intrusion methods,and the free oil content by using NMR fluid distribution secondary spectral stripping decomposition and logging.The research results contribute supplemental insights on continental shale oil deliverability in China,and provide a scientific basis for the rapid exploration and large-scale production of lacustrine shale oil.展开更多
The rapid development of electricity retail market has prompted an increasing number of electricity consumers to sign green electricity contracts with retail electricity companies,which poses greater challenges for th...The rapid development of electricity retail market has prompted an increasing number of electricity consumers to sign green electricity contracts with retail electricity companies,which poses greater challenges for the market service for green energy consumers.This study proposed a two-stage feature extraction approach for green energy consumers leveraging clustering and termfrequency-inverse document frequency(TF-IDF)algorithms within a knowledge graph framework to provide an information basis that supports the green development of the retail electricity market.First,the multi-source heterogeneous data of green energy consumers under an actual market environment is systematically introduced and the information is categorized into discrete,interval,and relational features.A clustering algorithm was employed to extract features of the trading behavior of green energy consumers in the first stage using the parameter data of green retail electricity contracts.Then,TF-IDF algorithm was applied in the second stage to extract features for green energy consumers in different clusters.Finally,the effectiveness of the proposed approach was validated based on the actual operational data in a southern province of China.It is shown that the most significant discrepancy between the retail trading behaviors of green energy consumers is the power share of green retail packages,whose averaged values are 25.64%,50%,39.66%,and 24.89%in four different clusters,respectively.Additionally,power supply bureaus and electricity retail companies affects the behavior of the green energy consumers most significantly.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 research optimized the structure of lithium extraction solar ponds to enhance the crystallization rate and yield of Li_(2)CO_(3).Using the response surface methodology in Design-Expert 10.0.3,the authors conducte...This research optimized the structure of lithium extraction solar ponds to enhance the crystallization rate and yield of Li_(2)CO_(3).Using the response surface methodology in Design-Expert 10.0.3,the authors conducted experiments to investigate the influence of four factors related to solar pond structure on the crystallization of Li_(2)CO_(3) and their pairwise interactions.Computational Fluid Dynamics(CFD)simulations of the flow field within the solar pond were performed using COMSOL Multiphysics software to compare temperature distributions before and after optimization.The results indicate that the optimal structure for lithium extraction from the Zabuye Salt Lake solar ponds includes UCZ(Upper Convective Zone)thickness of 53.63 cm,an LCZ(Lower Convective Zone)direct heating temperature of 57.39℃,a CO32−concentration of 32.21 g/L,and an added soda ash concentration of 6.52 g/L.Following this optimized pathway,the Li_(2)CO_(3) precipitation increased by 7.34% compared to the initial solar pond process,with a 33.33% improvement in lithium carbonate crystallization rate.This study demonstrates the feasibility of optimizing lithium extraction solar pond structures,offering a new approach for constructing such ponds in salt lakes.It provides valuable guidance for the efficient extraction of lithium resources from carbonate-type salt lake brines.展开更多
The titanium alloy strut serves as a key load-bearing component of aircraft landing gear,typically manufactured via forging.The friction condition has important influence on material flow and cavity filling during the...The titanium alloy strut serves as a key load-bearing component of aircraft landing gear,typically manufactured via forging.The friction condition has important influence on material flow and cavity filling during the forging process.Using the previously optimized shape and initial position of preform,the influence of the friction condition(friction factor m=0.1–0.3)on material flow and cavity filling was studied by numerical method with a shear friction model.A novel filling index was defined to reflect material flow into left and right flashes and zoom in on friction-induced results.The results indicate that the workpiece moves rigidly to the right direction,with the displacement decreasing as m increases.When m<0.18,the underfilling defect will occur in the left side of strut forging,while overflow occurs in the right forging die cavity.By combining the filling index and analyses of material flow and filling status,a reasonable friction factor interval of m=0.21–0.24 can be determined.Within this interval,the cavity filling behavior demonstrates robustness,with friction fluctuations exerting minimal influence.展开更多
Background:Ampelopsis grossedentata,vine tea,which is the tea alternative beverages in China.In vine tea processing,a large amount of broken tea is produced,which has low commercial value.Methods:This study investigat...Background:Ampelopsis grossedentata,vine tea,which is the tea alternative beverages in China.In vine tea processing,a large amount of broken tea is produced,which has low commercial value.Methods:This study investigates the influence of different extraction methods(room temperature water extraction,boiling water extraction,ultrasonic-assisted room temperature water extraction,and ultrasonic-assisted boiling water extraction,referred to as room temperature water extraction(RE),boiling water extraction(BE),ultrasonic assistance at room temperature water extraction(URE),and ultrasonic assistance in boiling water extraction(UBE))on the yield,dihydromyricetin(DMY)content,free amino acid composition,volatile aroma components,and antioxidant properties of vine tea extracts.Results:A notable influence of extraction temperature on the yield of vine tea extracts(P<0.05),with BE yielding the highest at 43.13±0.26%,higher than that of RE(34.29±0.81%).Ultrasound-assisted extraction significantly increased the DMY content of the extracts(P<0.05),whereas DMY content in the RE extracts was 59.94±1.70%,that of URE reached 66.14±2.78%.Analysis revealed 17 amino acids,with L-serine and aspartic acid being the most abundant in the extracts,nevertheless ultrasound-assisted extraction reduced total free amino acid content.Gas chromatography-mass spectrometry analysis demonstrated an increase in the diversity and quantity of compounds in the vine tea water extracts obtained through ultrasonic-assisted extraction.Specifically,69 and 68 volatile compounds were found in URE and UBE extracts,which were higher than the number found in RE and BE extracts.In vitro,antioxidant activity assessments revealed varying antioxidant capacities among different extraction methods,with RE exhibiting the highest DPPH scavenging rate,URE leading in ABTS•+free radical scavenging,and BE demonstrating superior ferric ion reducing antioxidant activity.Conclusion:The findings suggest that extraction methods significantly influence the chemical composition and antioxidant properties of vine tea extracts.Ultrasonic-assisted extraction proved instrumental in elevating the DMY content in vine tea extracts,thereby enriching its flavor profile while maintaining its antioxidant properties.展开更多
Accurately identifying building distribution from remote sensing images with complex background information is challenging.The emergence of diffusion models has prompted the innovative idea of employing the reverse de...Accurately identifying building distribution from remote sensing images with complex background information is challenging.The emergence of diffusion models has prompted the innovative idea of employing the reverse denoising process to distill building distribution from these complex backgrounds.Building on this concept,we propose a novel framework,building extraction diffusion model(BEDiff),which meticulously refines the extraction of building footprints from remote sensing images in a stepwise fashion.Our approach begins with the design of booster guidance,a mechanism that extracts structural and semantic features from remote sensing images to serve as priors,thereby providing targeted guidance for the diffusion process.Additionally,we introduce a cross-feature fusion module(CFM)that bridges the semantic gap between different types of features,facilitating the integration of the attributes extracted by booster guidance into the diffusion process more effectively.Our proposed BEDiff marks the first application of diffusion models to the task of building extraction.Empirical evidence from extensive experiments on the Beijing building dataset demonstrates the superior performance of BEDiff,affirming its effectiveness and potential for enhancing the accuracy of building extraction in complex urban landscapes.展开更多
This study aimed to investigate the effect of ultrasound-assisted alkaline extraction(UAE)(at 20 kHz and different powers of 0,200,300,400,500 and 600 W for 10 min)on the yield,structure and emulsifying properties of ...This study aimed to investigate the effect of ultrasound-assisted alkaline extraction(UAE)(at 20 kHz and different powers of 0,200,300,400,500 and 600 W for 10 min)on the yield,structure and emulsifying properties of chickpea protein isolate(CPI).Compared with the non-ultrasound group,ultrasound treatment at 400 W resulted in the largest increase in CPI yield,and both the particle size and turbidity decreased with increasing ultrasound power from 0 to 400 W.The scanning electron microscope results showed a uniform structural distribution of CPI.Moreover,itsα-helix content increased,β-sheet content decreased,and total sulfhydryl group content and endogenous fluorescence intensity rose,illustrating that UAE changed the secondary and tertiary structure of CPI.At 400 W,the solubility of the emulsion increased to 63.18%,and the best emulsifying properties were obtained;the emulsifying activity index(EAI)and emulsifying stability index(ESI)increased by 85.42%and 46.78%,respectively.Furthermore,the emulsion droplets formed were smaller and more uniform.In conclusion,proper UAE power conditions increased the extraction yield and protein content of CPI,and effectively improved its structure and emulsifying characteristics.展开更多
基金Supported by the National Natural Science Foundation of China(Nos.52293472,22473096 and 22471164)。
文摘Among various architectures of polymers,end-group-free rings have attracted growing interests due to their distinct physicochemical performances over the linear counterparts which are exemplified by reduced hydrodynamic size and slower degradation.It is key to develop facile methods to large-scale synthesis of polymer rings with tunable compositions and microstructures.Recent progresses in large-scale synthesis of polymer rings against single-chain dynamic nanoparticles,and the example applications in synchronous enhancing toughness and strength of polymer nanocomposites are summarized.Once there is the breakthrough in rational design and effective large-scale synthesis of polymer rings and their functional derivatives,a family of cyclic functional hybrids would be available,thus providing a new paradigm in developing polymer science and engineering.
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.
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.
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).The authors also acknowledge the Scientific Compass(http://www.shiyanjia.com)for the measurements.
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.
基金supported by the State Grid Science&Technology Project(5100-202114296A-0-0-00).
文摘This article introduces the concept of load aggregation,which involves a comprehensive analysis of loads to acquire their external characteristics for the purpose of modeling and analyzing power systems.The online identification method is a computer-involved approach for data collection,processing,and system identification,commonly used for adaptive control and prediction.This paper proposes a method for dynamically aggregating large-scale adjustable loads to support high proportions of new energy integration,aiming to study the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction methods.The experiment selected 300 central air conditioners as the research subject and analyzed their regulation characteristics,economic efficiency,and comfort.The experimental results show that as the adjustment time of the air conditioner increases from 5 minutes to 35 minutes,the stable adjustment quantity during the adjustment period decreases from 28.46 to 3.57,indicating that air conditioning loads can be controlled over a long period and have better adjustment effects in the short term.Overall,the experimental results of this paper demonstrate that analyzing the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction algorithms is effective.
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.
基金supported by the National Key Research and Development Program of China(2022YFE0206700)。
文摘1.Introduction Climate change mitigation pathways aimed at limiting global anthropogenic carbon dioxide(CO_(2))emissions while striving to constrain the global temperature increase to below 2℃—as outlined by the Intergovernmental Panel on Climate Change(IPCC)—consistently predict the widespread implementation of CO_(2)geological storage on a global scale.
基金Project supported by the National Natural Science Foundation of China(52074031)the Key Research and Development Program of Shandong Province(ZR2021MB051,ZR2020ME256)the Open Project of Key Laboratory of Green Chemical Engineering Process of Ministry of Education(GCP202117)。
文摘Solvent extraction is the main method used to separate and purify rare earth elements.In the process of rare earths extraction,emulsification often generated due to the instability of the aqueous and organic phases or improper operating conditions.Once emulsification occurs,it would not only lead to low rare earths recovery efficiency,small product quantities,high production costs and the losing of extractant and rare earth resources,but also result in serious environmental pollution.Therefore,it is very important to study the micro-mechanisms of emulsification and establish new methods to prevent emulsification at the source.In this paper,possible factors resulting in emulsification,such as the compositions and properties of the organic and aqueous phases,the operating conditions of the rare earths extraction are reviewed.The micro-mechanisms of emulsification are summarized basing on the microscopic structures in the bulk phase,aggregations of the extractants at the organic-aqueous interface,spectral characterizations and computational simulations.On this basis,new formation mechanisms are proposed for emulsification.Preliminary explorations are employed to verify the correctness of these new viewpoints.Finally,future directions for studies of the emulsification micro-mechanism are proposed.This study provides a theoretical basis for further understanding the micro-mechanisms of interfacial instability resulting in emulsification in the process of rare earths extraction.
基金supported by the National Key Research&Development Program of China(Grant No.2023YFC3008404)the Key Laboratory of Earth Fissures Geological Disaster,Ministry of Natural Resources,China(Grant Nos.EFGD20240609 and EFGD20240610).
文摘The recent upsurge in metro construction emphasizes the necessity of understanding the mechanical performance of metro shield tunnel subjected to the influence of ground fissures.In this study,a largescale experiment,in combination with numerical simulation,was conducted to investigate the influence of ground fissures on a metro shield tunnel.The results indicate that the lining contact pressure at the vault increases in the hanging wall while decreases in the footwall,resulting in a two-dimensional stress state of vertical shear and axial tension-compression,and simultaneous vertical dislocation and axial tilt for the segments around the ground fissure.In addition,the damage to curved bolts includes tensile yield,flexural yield,and shear twist,leading to obvious concrete lining damage,particularly at the vault,arch bottom,and hance,indicating that the joints in these positions are weak areas.The shield tunnel orthogonal to the ground fissure ultimately experiences shear failure,suggesting that the maximum actual dislocation of ground fissure that the structure can withstand is approximately 20 cm,and five segment rings in the hanging wall and six segment rings in the footwall also need to be reinforced.This study could provide a reference for metro design in ground fissure sites.
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 the National Key R&D Program of China(2024YFE0114000)Science and Technology Project of China National Petroleum Corporation(2024DJ8702).
文摘Based on the analysis of typical lacustrine shale oil zones in China and their geological characteristics,this study elucidates the fundamental differences between the enrichment patterns of shale oil sweet spots and conventional oil and gas.The key parameters and evaluation methods for assessing the large-scale production potential of lacustrine shale oil are proposed.The results show that shale oil is a petroleum resource that exists in organic-rich shale formations,in other words,it is preserved in its source bed,following a different process of generation-accumulation-enrichment from conventional oil and gas.Thus,the concept of“reservoir”seems to be inapplicable to shale oil.In China,lacustrine shale oil is distributed widely,but the geological characteristics and sweet spots enrichment patterns of shale oil vary significantly in lacustrine basins where the water environment and the tectonic evolution and diagenetic transformation frameworks are distinct.The core of the evaluation of lacustrine shale oil is“sweet spot volume”.The key factors for evaluating the large-scale production of continental shale oil are the oil storage capacity,oil-bearing capacity and oil producing capacity.The key parameters for evaluating these capacities are total porosity,oil content,and free oil content,respectively.It is recommended to determine the total porosity of shale by combining helium porosity measurement with nuclear magnetic resonance(NMR)method,the oil content of key layers by using organic solvent extraction,NMR method and high pressure mercury intrusion methods,and the free oil content by using NMR fluid distribution secondary spectral stripping decomposition and logging.The research results contribute supplemental insights on continental shale oil deliverability in China,and provide a scientific basis for the rapid exploration and large-scale production of lacustrine shale oil.
基金support by the Science and Technology Project of Guangdong Power Exchange Center Co.,Ltd.(No.GDKJXM20222599)National Natural Science Foundation of China(No.52207104)Natural Science Foundation of Guangdong Province(No.2024A1515010426).
文摘The rapid development of electricity retail market has prompted an increasing number of electricity consumers to sign green electricity contracts with retail electricity companies,which poses greater challenges for the market service for green energy consumers.This study proposed a two-stage feature extraction approach for green energy consumers leveraging clustering and termfrequency-inverse document frequency(TF-IDF)algorithms within a knowledge graph framework to provide an information basis that supports the green development of the retail electricity market.First,the multi-source heterogeneous data of green energy consumers under an actual market environment is systematically introduced and the information is categorized into discrete,interval,and relational features.A clustering algorithm was employed to extract features of the trading behavior of green energy consumers in the first stage using the parameter data of green retail electricity contracts.Then,TF-IDF algorithm was applied in the second stage to extract features for green energy consumers in different clusters.Finally,the effectiveness of the proposed approach was validated based on the actual operational data in a southern province of China.It is shown that the most significant discrepancy between the retail trading behaviors of green energy consumers is the power share of green retail packages,whose averaged values are 25.64%,50%,39.66%,and 24.89%in four different clusters,respectively.Additionally,power supply bureaus and electricity retail companies affects the behavior of the green energy consumers most significantly.
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This study was supported by the National Natural Science Foundation of China(U20A20148)the Major Science and Technology Projects of the Xizang(Tibet)Autonomous Region(XZ202201ZD0004G and XZ202201ZD0004G01).
文摘This research optimized the structure of lithium extraction solar ponds to enhance the crystallization rate and yield of Li_(2)CO_(3).Using the response surface methodology in Design-Expert 10.0.3,the authors conducted experiments to investigate the influence of four factors related to solar pond structure on the crystallization of Li_(2)CO_(3) and their pairwise interactions.Computational Fluid Dynamics(CFD)simulations of the flow field within the solar pond were performed using COMSOL Multiphysics software to compare temperature distributions before and after optimization.The results indicate that the optimal structure for lithium extraction from the Zabuye Salt Lake solar ponds includes UCZ(Upper Convective Zone)thickness of 53.63 cm,an LCZ(Lower Convective Zone)direct heating temperature of 57.39℃,a CO32−concentration of 32.21 g/L,and an added soda ash concentration of 6.52 g/L.Following this optimized pathway,the Li_(2)CO_(3) precipitation increased by 7.34% compared to the initial solar pond process,with a 33.33% improvement in lithium carbonate crystallization rate.This study demonstrates the feasibility of optimizing lithium extraction solar pond structures,offering a new approach for constructing such ponds in salt lakes.It provides valuable guidance for the efficient extraction of lithium resources from carbonate-type salt lake brines.
基金National Natural Science Foundation of China(52375378)National Key Laboratory of Metal Forming Technology and Heavy Equipment(S2308100.W12)Huxiang High-Level Talent Gathering Project of Hunan Province(2021RC5001)。
文摘The titanium alloy strut serves as a key load-bearing component of aircraft landing gear,typically manufactured via forging.The friction condition has important influence on material flow and cavity filling during the forging process.Using the previously optimized shape and initial position of preform,the influence of the friction condition(friction factor m=0.1–0.3)on material flow and cavity filling was studied by numerical method with a shear friction model.A novel filling index was defined to reflect material flow into left and right flashes and zoom in on friction-induced results.The results indicate that the workpiece moves rigidly to the right direction,with the displacement decreasing as m increases.When m<0.18,the underfilling defect will occur in the left side of strut forging,while overflow occurs in the right forging die cavity.By combining the filling index and analyses of material flow and filling status,a reasonable friction factor interval of m=0.21–0.24 can be determined.Within this interval,the cavity filling behavior demonstrates robustness,with friction fluctuations exerting minimal influence.
基金supported by the Key Research and Development Program of Hunan Province of China(No.2022NK2036)Xiangxi Prefecture Science and Technology Plan Project"School-Local Integration"Special Project(No.2022001)the scientific research project of Hunan Provincial Department of Education(No.22B0520).
文摘Background:Ampelopsis grossedentata,vine tea,which is the tea alternative beverages in China.In vine tea processing,a large amount of broken tea is produced,which has low commercial value.Methods:This study investigates the influence of different extraction methods(room temperature water extraction,boiling water extraction,ultrasonic-assisted room temperature water extraction,and ultrasonic-assisted boiling water extraction,referred to as room temperature water extraction(RE),boiling water extraction(BE),ultrasonic assistance at room temperature water extraction(URE),and ultrasonic assistance in boiling water extraction(UBE))on the yield,dihydromyricetin(DMY)content,free amino acid composition,volatile aroma components,and antioxidant properties of vine tea extracts.Results:A notable influence of extraction temperature on the yield of vine tea extracts(P<0.05),with BE yielding the highest at 43.13±0.26%,higher than that of RE(34.29±0.81%).Ultrasound-assisted extraction significantly increased the DMY content of the extracts(P<0.05),whereas DMY content in the RE extracts was 59.94±1.70%,that of URE reached 66.14±2.78%.Analysis revealed 17 amino acids,with L-serine and aspartic acid being the most abundant in the extracts,nevertheless ultrasound-assisted extraction reduced total free amino acid content.Gas chromatography-mass spectrometry analysis demonstrated an increase in the diversity and quantity of compounds in the vine tea water extracts obtained through ultrasonic-assisted extraction.Specifically,69 and 68 volatile compounds were found in URE and UBE extracts,which were higher than the number found in RE and BE extracts.In vitro,antioxidant activity assessments revealed varying antioxidant capacities among different extraction methods,with RE exhibiting the highest DPPH scavenging rate,URE leading in ABTS•+free radical scavenging,and BE demonstrating superior ferric ion reducing antioxidant activity.Conclusion:The findings suggest that extraction methods significantly influence the chemical composition and antioxidant properties of vine tea extracts.Ultrasonic-assisted extraction proved instrumental in elevating the DMY content in vine tea extracts,thereby enriching its flavor profile while maintaining its antioxidant properties.
基金supported by the National Natural Science Foundation of China(Nos.61906168,62202429 and 62272267)the Zhejiang Provincial Natural Science Foundation of China(No.LY23F020023)the Construction of Hubei Provincial Key Laboratory for Intelligent Visual Monitoring of Hydropower Projects(No.2022SDSJ01)。
文摘Accurately identifying building distribution from remote sensing images with complex background information is challenging.The emergence of diffusion models has prompted the innovative idea of employing the reverse denoising process to distill building distribution from these complex backgrounds.Building on this concept,we propose a novel framework,building extraction diffusion model(BEDiff),which meticulously refines the extraction of building footprints from remote sensing images in a stepwise fashion.Our approach begins with the design of booster guidance,a mechanism that extracts structural and semantic features from remote sensing images to serve as priors,thereby providing targeted guidance for the diffusion process.Additionally,we introduce a cross-feature fusion module(CFM)that bridges the semantic gap between different types of features,facilitating the integration of the attributes extracted by booster guidance into the diffusion process more effectively.Our proposed BEDiff marks the first application of diffusion models to the task of building extraction.Empirical evidence from extensive experiments on the Beijing building dataset demonstrates the superior performance of BEDiff,affirming its effectiveness and potential for enhancing the accuracy of building extraction in complex urban landscapes.
文摘This study aimed to investigate the effect of ultrasound-assisted alkaline extraction(UAE)(at 20 kHz and different powers of 0,200,300,400,500 and 600 W for 10 min)on the yield,structure and emulsifying properties of chickpea protein isolate(CPI).Compared with the non-ultrasound group,ultrasound treatment at 400 W resulted in the largest increase in CPI yield,and both the particle size and turbidity decreased with increasing ultrasound power from 0 to 400 W.The scanning electron microscope results showed a uniform structural distribution of CPI.Moreover,itsα-helix content increased,β-sheet content decreased,and total sulfhydryl group content and endogenous fluorescence intensity rose,illustrating that UAE changed the secondary and tertiary structure of CPI.At 400 W,the solubility of the emulsion increased to 63.18%,and the best emulsifying properties were obtained;the emulsifying activity index(EAI)and emulsifying stability index(ESI)increased by 85.42%and 46.78%,respectively.Furthermore,the emulsion droplets formed were smaller and more uniform.In conclusion,proper UAE power conditions increased the extraction yield and protein content of CPI,and effectively improved its structure and emulsifying characteristics.
