Electrochemical insertion/extraction of Li on cathode materials of spinel type LiMn2O4 and ordered rock-salt type LiCo0.5 Ni0.5O2 was measured on samples of which structures were well characterized. On the basis of ex...Electrochemical insertion/extraction of Li on cathode materials of spinel type LiMn2O4 and ordered rock-salt type LiCo0.5 Ni0.5O2 was measured on samples of which structures were well characterized. On the basis of experimental results on structure, morphology and charge-discharge characteristics, the effect of crystallinity of the cathode materiaIs on electrochemical Li insertion/extraction performance was discussed. These two transition metal oxides belong to onegroup that the crystallinity of these oxides affects to the performance.展开更多
Rechargeable aqueous zinc ion batteries(AZIBs)were considered as one of the most promising candidates for large-scale energy storage due to the merits of high safety and inexpensiveness.As AZIBs cathode material,Mn O_...Rechargeable aqueous zinc ion batteries(AZIBs)were considered as one of the most promising candidates for large-scale energy storage due to the merits of high safety and inexpensiveness.As AZIBs cathode material,Mn O_(2)possesses great merits but was greatly hindered due to the sluggish diffusion kinetic of Zn^(2+) during electrochemical operations.Herein,deep Zn^(2+) ions intercalatedδ-Mn O_(2)(Zn-Mn O_(2))was achieved by the in situ electrochemical deposition route,which significantly enhanced the diffusion ability of Zn^(2+) due to the synergistic effects of Zn^(2+) pillars and structural H;O.The resultant Zn-Mn O_(2)based AZIBs delivers a record capacity of 696 m Ah/g(0.5 m Ah/cm^(2))based on the initial mass loading,which is approaching the theoretical capacity of Mn O_(2)with a two-electrons reaction.In-situ Raman studies reveal highly reversible Zn^(2+)ions insertion/extraction behaviors and here the Zn-Mn O_(2)plays the role of a container during the charge–discharge process.Further charge storage mechanism investigations point out the insertion/extraction of Zn^(2+) and H^(+) coincides,and such process is significantly facilitated results from superior interlayered configurations of Zn-Mn O_(2)The excellent electrochemical performance of Zn-Mn O_(2)achieved in this work suggests the deep ions pre-intercalation strategy may aid in the future development of advanced cathodes for AZIBs.展开更多
Electrochemical insertion/extraction of Li on cathode materials of anatase type TiO_2, quasilayered structure V_2O_5 and layered structure MoO_3 was measured on samples of which structures were well characterized and...Electrochemical insertion/extraction of Li on cathode materials of anatase type TiO_2, quasilayered structure V_2O_5 and layered structure MoO_3 was measured on samples of which structures were well characterized and showed a wide range of crystallinity. On the basis of experimental results on structure, morphology and charge-discharge characteristics, the effect of crystallinity of the cathode materials on electrochemical Li insertion/extraction pedermance was discussed. These three transition metal oxides were classified as one group on the basis of whether the crystallinity of these oxides affects to the performance or not; LiMn_2O_4 and LiCo_(0.5)O_2 belongs to the former group and TiO_2, V_2O_5 and MoO_3 to the latter.展开更多
The work distills the main mechanisms during the lithium insertion/extraction of LiFePO_4 cathode materials. The "diffusion-controlled" and "phase-boundary controlled" mechanism are especially illu...The work distills the main mechanisms during the lithium insertion/extraction of LiFePO_4 cathode materials. The "diffusion-controlled" and "phase-boundary controlled" mechanism are especially illustrated. Meanwhile, some recent observation and analyses by in-situ or in operando on the Li-insertion/extraction of LiFePO_4 are summarized and prospected.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
An inverse spinel-type metal oxide, magnesium-manganese-titanium oxide （Mg2Mn0.5Ti0.5O4）, were prepared using the coprecipitation/thermal crystallization method. The extraction/insertion reaction with this material ...An inverse spinel-type metal oxide, magnesium-manganese-titanium oxide （Mg2Mn0.5Ti0.5O4）, were prepared using the coprecipitation/thermal crystallization method. The extraction/insertion reaction with this material was investigated by X-ray, saturation capacity of exchange, pH titration, and distribution coefficient （Kd） measurement. The acid treatments of Mg2Mn0.5Ti0.5O4 caused Mg^2＋ extractions of more than 81%, whereas the dissolutions of Mn^4＋ and Ti^4＋ were less than 10%. The experimental results proved that the acid-treated sample has a capacity of exchange 56 mg·g^-1 for Li^＋ in the solution. The chemical analysis showed that the Li^＋ extraction/insertion progressed mainly by ion-exchange mechanism and surface adsorption.展开更多
In order to improve the effectiveness of percutaneous diagnosis and therapies, the needle insertion into the deforming soft and inhomogenous tissue should be accurate. In this study a needle with 6 degrees of freedom ...In order to improve the effectiveness of percutaneous diagnosis and therapies, the needle insertion into the deforming soft and inhomogenous tissue should be accurate. In this study a needle with 6 degrees of freedom force/torque sensor is used to find the relationship between the pathway＇s length and the force. Our experiments show that the method with repeated extraction-insertion cy- cles can make the needle approach the target as much as possible. Meanwhile a method to obtain the appropriaterepeated extraction-insertion cycles is given to drive the needle to execute the repeat- ed cycles efficiently. Experiments and discussions were conducted to preliminarily validate the meth- od.展开更多
The vast availability of information sources has created a need for research on automatic summarization. Current methods perform either by extraction or abstraction. The extraction methods are interesting, because the...The vast availability of information sources has created a need for research on automatic summarization. Current methods perform either by extraction or abstraction. The extraction methods are interesting, because they are robust and independent of the language used. An extractive summary is obtained by selecting sentences of the original source based on information content. This selection can be automated using a classification function induced by a machine learning algorithm. This function classifies sentences into two groups: important or non-important. The important sentences then form the summary. But, the efficiency of this function directly depends on the used training set to induce it. This paper proposes an original way of optimizing this training set by inserting lexemes obtained from ontological knowledge bases. The training set optimized is reinforced by ontological knowledge. An experiment with four machine learning algorithms was made to validate this proposition. The improvement achieved is clearly significant for each of these algorithms.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
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 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
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
An efficient TfOH-catalyzed O—H insertion reaction of α-aryl diazoesters with carboxylic acids is reported.This metal-free protocol provides an operationally simple method for a one-pot assembly of diverse α-acylox...An efficient TfOH-catalyzed O—H insertion reaction of α-aryl diazoesters with carboxylic acids is reported.This metal-free protocol provides an operationally simple method for a one-pot assembly of diverse α-acyloxy esters in moderate to high yields with a broad substrate scope.All starting materials are readily available,and the reactions can be conducted in the open air at room temperature.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
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
A blue light-induced formal insertion reaction ofα-siloxy carbene into the C—H bond of 1,3-diketones has been reported.Under the irradiation of blue light,acylsilane converts toα-siloxy carbene,which then undergoes...A blue light-induced formal insertion reaction ofα-siloxy carbene into the C—H bond of 1,3-diketones has been reported.Under the irradiation of blue light,acylsilane converts toα-siloxy carbene,which then undergoes formal C—H bond insertion reaction with the enol form of 1,3-diketone.This method uses readily available and relative stable acylsilane as car-bene precursor,which features a simple and metal-free approach under mild conditions.Moreover,the synthetic potential of this protocol has been demonstrated by performing the reaction on a gram scale with comparable high yield.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
With the rapid expansion of social media,analyzing emotions and their causes in texts has gained significant importance.Emotion-cause pair extraction enables the identification of causal relationships between emotions...With the rapid expansion of social media,analyzing emotions and their causes in texts has gained significant importance.Emotion-cause pair extraction enables the identification of causal relationships between emotions and their triggers within a text,facilitating a deeper understanding of expressed sentiments and their underlying reasons.This comprehension is crucial for making informed strategic decisions in various business and societal contexts.However,recent research approaches employing multi-task learning frameworks for modeling often face challenges such as the inability to simultaneouslymodel extracted features and their interactions,or inconsistencies in label prediction between emotion-cause pair extraction and independent assistant tasks like emotion and cause extraction.To address these issues,this study proposes an emotion-cause pair extraction methodology that incorporates joint feature encoding and task alignment mechanisms.The model consists of two primary components:First,joint feature encoding simultaneously generates features for emotion-cause pairs and clauses,enhancing feature interactions between emotion clauses,cause clauses,and emotion-cause pairs.Second,the task alignment technique is applied to reduce the labeling distance between emotion-cause pair extraction and the two assistant tasks,capturing deep semantic information interactions among tasks.The proposed method is evaluated on a Chinese benchmark corpus using 10-fold cross-validation,assessing key performance metrics such as precision,recall,and F1 score.Experimental results demonstrate that the model achieves an F1 score of 76.05%,surpassing the state-of-the-art by 1.03%.The proposed model exhibits significant improvements in emotion-cause pair extraction(ECPE)and cause extraction(CE)compared to existing methods,validating its effectiveness.This research introduces a novel approach based on joint feature encoding and task alignment mechanisms,contributing to advancements in emotion-cause pair extraction.However,the study’s limitation lies in the data sources,potentially restricting the generalizability of the findings.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 physical examination of the fruit of soursop fruit (Annona muricata) selected from different parent trees was investigated. Three-stage modified Soxhlet method was used which includes a percolator (boiler and refl...The physical examination of the fruit of soursop fruit (Annona muricata) selected from different parent trees was investigated. Three-stage modified Soxhlet method was used which includes a percolator (boiler and reflux) which circulates the solvent, a thimble (usually made of thick filter paper) which retains the seed to be extracted, and a siphon mechanism, which periodically empties the condensed solvent from the thimble back into the percolator. The extraction of oil from the seed and the percentage yield was examined. The oil samples were characterized for physico-chemical properties. The maximum values of physical parameters found were fruit weight 3.7 ± 7.09, fruit length 12.2 ± 28.3 cm, with 15.2 ± 20.81 cm and 0.12 ± 18.91 g for pulp weight. The percentage oil yield of 48.5% was obtained due to the environmental factors such as the soil type, planting season and optimal temperature of the region of seed cultivation. The result of chemical properties showed maximum acid value 0.46 mg KOH, FFA of 0.33 mg, saponification of 189.4 mg KOH mg and peroxide value of 4.33 mg/g. The oil physical properties as discovered have a melting point of 32˚C, smoke point of 198˚C and flash point of 280˚C. The results obtained in this study further reveal the potential of oil from seed of soursop as a substitute for conventional vegetable oil due to its high flash point which is an indication of its low flammability and can be used as a good source of food, industrially can be used as an anti-microbial agent and for pest control.展开更多
文摘Electrochemical insertion/extraction of Li on cathode materials of spinel type LiMn2O4 and ordered rock-salt type LiCo0.5 Ni0.5O2 was measured on samples of which structures were well characterized. On the basis of experimental results on structure, morphology and charge-discharge characteristics, the effect of crystallinity of the cathode materiaIs on electrochemical Li insertion/extraction performance was discussed. These two transition metal oxides belong to onegroup that the crystallinity of these oxides affects to the performance.
基金financially supported by the National Natural Science Foundation of China(Nos.51772138,51572118,and 51601082)the Fundamental Research Funds for the Central Universities(No.lzujbky-2020-59)。
文摘Rechargeable aqueous zinc ion batteries(AZIBs)were considered as one of the most promising candidates for large-scale energy storage due to the merits of high safety and inexpensiveness.As AZIBs cathode material,Mn O_(2)possesses great merits but was greatly hindered due to the sluggish diffusion kinetic of Zn^(2+) during electrochemical operations.Herein,deep Zn^(2+) ions intercalatedδ-Mn O_(2)(Zn-Mn O_(2))was achieved by the in situ electrochemical deposition route,which significantly enhanced the diffusion ability of Zn^(2+) due to the synergistic effects of Zn^(2+) pillars and structural H;O.The resultant Zn-Mn O_(2)based AZIBs delivers a record capacity of 696 m Ah/g(0.5 m Ah/cm^(2))based on the initial mass loading,which is approaching the theoretical capacity of Mn O_(2)with a two-electrons reaction.In-situ Raman studies reveal highly reversible Zn^(2+)ions insertion/extraction behaviors and here the Zn-Mn O_(2)plays the role of a container during the charge–discharge process.Further charge storage mechanism investigations point out the insertion/extraction of Zn^(2+) and H^(+) coincides,and such process is significantly facilitated results from superior interlayered configurations of Zn-Mn O_(2)The excellent electrochemical performance of Zn-Mn O_(2)achieved in this work suggests the deep ions pre-intercalation strategy may aid in the future development of advanced cathodes for AZIBs.
文摘Electrochemical insertion/extraction of Li on cathode materials of anatase type TiO_2, quasilayered structure V_2O_5 and layered structure MoO_3 was measured on samples of which structures were well characterized and showed a wide range of crystallinity. On the basis of experimental results on structure, morphology and charge-discharge characteristics, the effect of crystallinity of the cathode materials on electrochemical Li insertion/extraction pedermance was discussed. These three transition metal oxides were classified as one group on the basis of whether the crystallinity of these oxides affects to the performance or not; LiMn_2O_4 and LiCo_(0.5)O_2 belongs to the former group and TiO_2, V_2O_5 and MoO_3 to the latter.
基金supported by the National Natural Science Foundation of China(No.51504196)Key Research and Development Plan of Shaanxi Province(No.2017ZDXM-GY-039)
文摘The work distills the main mechanisms during the lithium insertion/extraction of LiFePO_4 cathode materials. The "diffusion-controlled" and "phase-boundary controlled" mechanism are especially illustrated. Meanwhile, some recent observation and analyses by in-situ or in operando on the Li-insertion/extraction of LiFePO_4 are summarized and prospected.
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An inverse spinel-type metal oxide, magnesium-manganese-titanium oxide （Mg2Mn0.5Ti0.5O4）, were prepared using the coprecipitation/thermal crystallization method. The extraction/insertion reaction with this material was investigated by X-ray, saturation capacity of exchange, pH titration, and distribution coefficient （Kd） measurement. The acid treatments of Mg2Mn0.5Ti0.5O4 caused Mg^2＋ extractions of more than 81%, whereas the dissolutions of Mn^4＋ and Ti^4＋ were less than 10%. The experimental results proved that the acid-treated sample has a capacity of exchange 56 mg·g^-1 for Li^＋ in the solution. The chemical analysis showed that the Li^＋ extraction/insertion progressed mainly by ion-exchange mechanism and surface adsorption.
基金Supported by the National Natural Science Foundation of Scientific Instruments Basis of Special(51127004)the National Natural Science Foundation of Youth Science Foundation(51105036)High-quality CNC Machine-Tool and Basic Manufacturing Equipment Scientific Major Project(2012ZX04010-061)
文摘In order to improve the effectiveness of percutaneous diagnosis and therapies, the needle insertion into the deforming soft and inhomogenous tissue should be accurate. In this study a needle with 6 degrees of freedom force/torque sensor is used to find the relationship between the pathway＇s length and the force. Our experiments show that the method with repeated extraction-insertion cy- cles can make the needle approach the target as much as possible. Meanwhile a method to obtain the appropriaterepeated extraction-insertion cycles is given to drive the needle to execute the repeat- ed cycles efficiently. Experiments and discussions were conducted to preliminarily validate the meth- od.
文摘The vast availability of information sources has created a need for research on automatic summarization. Current methods perform either by extraction or abstraction. The extraction methods are interesting, because they are robust and independent of the language used. An extractive summary is obtained by selecting sentences of the original source based on information content. This selection can be automated using a classification function induced by a machine learning algorithm. This function classifies sentences into two groups: important or non-important. The important sentences then form the summary. But, the efficiency of this function directly depends on the used training set to induce it. This paper proposes an original way of optimizing this training set by inserting lexemes obtained from ontological knowledge bases. The training set optimized is reinforced by ontological knowledge. An experiment with four machine learning algorithms was made to validate this proposition. The improvement achieved is clearly significant for each of these algorithms.
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.
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.
文摘An efficient TfOH-catalyzed O—H insertion reaction of α-aryl diazoesters with carboxylic acids is reported.This metal-free protocol provides an operationally simple method for a one-pot assembly of diverse α-acyloxy esters in moderate to high yields with a broad substrate scope.All starting materials are readily available,and the reactions can be conducted in the open air at room temperature.
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.
文摘A blue light-induced formal insertion reaction ofα-siloxy carbene into the C—H bond of 1,3-diketones has been reported.Under the irradiation of blue light,acylsilane converts toα-siloxy carbene,which then undergoes formal C—H bond insertion reaction with the enol form of 1,3-diketone.This method uses readily available and relative stable acylsilane as car-bene precursor,which features a simple and metal-free approach under mild conditions.Moreover,the synthetic potential of this protocol has been demonstrated by performing the reaction on a gram scale with comparable high yield.
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.
文摘With the rapid expansion of social media,analyzing emotions and their causes in texts has gained significant importance.Emotion-cause pair extraction enables the identification of causal relationships between emotions and their triggers within a text,facilitating a deeper understanding of expressed sentiments and their underlying reasons.This comprehension is crucial for making informed strategic decisions in various business and societal contexts.However,recent research approaches employing multi-task learning frameworks for modeling often face challenges such as the inability to simultaneouslymodel extracted features and their interactions,or inconsistencies in label prediction between emotion-cause pair extraction and independent assistant tasks like emotion and cause extraction.To address these issues,this study proposes an emotion-cause pair extraction methodology that incorporates joint feature encoding and task alignment mechanisms.The model consists of two primary components:First,joint feature encoding simultaneously generates features for emotion-cause pairs and clauses,enhancing feature interactions between emotion clauses,cause clauses,and emotion-cause pairs.Second,the task alignment technique is applied to reduce the labeling distance between emotion-cause pair extraction and the two assistant tasks,capturing deep semantic information interactions among tasks.The proposed method is evaluated on a Chinese benchmark corpus using 10-fold cross-validation,assessing key performance metrics such as precision,recall,and F1 score.Experimental results demonstrate that the model achieves an F1 score of 76.05%,surpassing the state-of-the-art by 1.03%.The proposed model exhibits significant improvements in emotion-cause pair extraction(ECPE)and cause extraction(CE)compared to existing methods,validating its effectiveness.This research introduces a novel approach based on joint feature encoding and task alignment mechanisms,contributing to advancements in emotion-cause pair extraction.However,the study’s limitation lies in the data sources,potentially restricting the generalizability of the findings.
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.
文摘The physical examination of the fruit of soursop fruit (Annona muricata) selected from different parent trees was investigated. Three-stage modified Soxhlet method was used which includes a percolator (boiler and reflux) which circulates the solvent, a thimble (usually made of thick filter paper) which retains the seed to be extracted, and a siphon mechanism, which periodically empties the condensed solvent from the thimble back into the percolator. The extraction of oil from the seed and the percentage yield was examined. The oil samples were characterized for physico-chemical properties. The maximum values of physical parameters found were fruit weight 3.7 ± 7.09, fruit length 12.2 ± 28.3 cm, with 15.2 ± 20.81 cm and 0.12 ± 18.91 g for pulp weight. The percentage oil yield of 48.5% was obtained due to the environmental factors such as the soil type, planting season and optimal temperature of the region of seed cultivation. The result of chemical properties showed maximum acid value 0.46 mg KOH, FFA of 0.33 mg, saponification of 189.4 mg KOH mg and peroxide value of 4.33 mg/g. The oil physical properties as discovered have a melting point of 32˚C, smoke point of 198˚C and flash point of 280˚C. The results obtained in this study further reveal the potential of oil from seed of soursop as a substitute for conventional vegetable oil due to its high flash point which is an indication of its low flammability and can be used as a good source of food, industrially can be used as an anti-microbial agent and for pest control.
