Conventional locking/release mechanisms often face challenges in aircraft wing separation processes,such as excessive impact loads and insufficient synchronization.These may cause structural damage to the airframe or ...Conventional locking/release mechanisms often face challenges in aircraft wing separation processes,such as excessive impact loads and insufficient synchronization.These may cause structural damage to the airframe or attitude instability,seriously compromising mission reliability.To address this engineering challenge,this paper proposes a multi-point low-impact locking/release mechanism based on the mobility model and energy conversion strategy.Through establishing a DOF constraint framework system,this paper systematically analyzes the energy transfer and conversion characteristics during the wing separation process,reveals the generation mechanism of impact loads,and conducts research on low-impact design based on energy conversion strategy.Building on this foundation,a single-point locking/release mechanism employing parallel trapezoidal key shaft structure was designed,which increases frictional contact time and reduces the energy release rate,thereby achieving low-impact characteristics.The mechanism's performance was validated through physical prototype development and systematic functional testing(including unlocking force,synchronization,and impact tests).Experimental results demonstrate:(1)Under 14 kN preload condition,the maximum unlocking force was only 92.54 N,showing a linear relationship with preload that satisfies the"strong-connection/weak-unlock"design requirement;(2)Wing separation was completed within 46 ms,with synchronization time difference among three separation mechanisms stably controlled within 12-14 ms,proving rapid and reliable operation;(3)The unlocking impact acceleration ranged between 26 and 73 g,below the 100 g design limit,confirming the effectiveness of the energy conversion strategy.The proposed low-impact locking/release mechanism design method based on energy conversion strategy resolves the traditional challenges of high impact and synchronization deficiencies.The synergistic optimization mechanism of"structural load reduction and performance improvement"provides a highly reliable technical solution for wing separable mechanisms while offering novel design insights for wing connection/separation systems engineering.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
AIM:To investigate the long-term outcomes in acute primary angle closure(APAC)patients treated with lens extraction(LE)surgery and to identify risk factors for glaucomatous optic neuropathy(GON).METHODS:In this longit...AIM:To investigate the long-term outcomes in acute primary angle closure(APAC)patients treated with lens extraction(LE)surgery and to identify risk factors for glaucomatous optic neuropathy(GON).METHODS:In this longitudinal observational study,detailed medical histories of APAC patients and comprehensive ophthalmic examinations at final followup were collected.Logistic regression analysis was performed to identify predictors of blindness.Univariate and multivariate linear regression analyses were conducted to determine risk factors associated with visual outcomes.RESULTS:This study included 39 affected eyes of 31 subjects(26 females)with an average age of 74.1±8.0y.At 6.7±4.2y after APAC attack,2(5.7%)eyes had bestcorrected visual acuity(VA)worse than 3/60.Advanced glaucomatous visual field loss was observed in 15(39.5%)affected eyes and 5(25.0%)fellow eyes.Nine affected eyes(23.7%)had GON,and 11(28.9%)were blind.Six(15.4%)affected eyes and 2(9.1%)fellow eyes had suspicious progression.A significantly higher blindness rate in factory workers compared to office workers.Logistic regression identified that worse VA at attack(OR 10.568,95%CI 1.288-86.695;P=0.028)and worse early postoperative VA(OR 13.214,95%CI 1.157-150.881;P=0.038)were risk factors for blindness.Multivariate regression showed that longer duration of elevated intraocular pressure(P=0.004)and worse early postoperative VA(P=0.009)were associated with worse visual outcomes.CONCLUSION:Despite LE surgery,some APAC patients experience continued visual function deterioration.Lifelong monitoring is necessary.Target pressure and progression rates should be re-evaluated during follow-up.展开更多
An acid sulfate soil sample was successively extracted with deionized water, 1 mol L-1 KCl and 0.000 5 mol L-l Ca(OH)2 solutions. The results showed that only very small amounts of acidity were extracted by deionized ...An acid sulfate soil sample was successively extracted with deionized water, 1 mol L-1 KCl and 0.000 5 mol L-l Ca(OH)2 solutions. The results showed that only very small amounts of acidity were extracted by deionized water, possibly through slow jarosite hydrolysis. Acid release through jarosite hydrolysis was greatly enhanced by Ca(OH)2 extraction at the expense of the added OH- being neutralized by the acid released. Successive extraction of the sample with KCl removed the largest amounts of acidity from the sample. However, it is likely that the major form of acidity released by KCl extraction was exchangeable acidity. The results also show the occurrence of low or non charged Al and Fe species in water and Ca(OH)2 extracts after first a few extractions. It appears that such a phenomenon was related to a decreasing EC value with increasing number of extractions.展开更多
A simulating experiment was carried out on the interaction between natural precipitation and soil. The results demonstrated that the contents of heavy metals (V, Co, Cr, and Ni) released from soil into the solution un...A simulating experiment was carried out on the interaction between natural precipitation and soil. The results demonstrated that the contents of heavy metals (V, Co, Cr, and Ni) released from soil into the solution under Earth’s surface conditions are higher than the contents of those metals bonded to exchangeable species, which were extracted by sequential extraction procedure recommended by Tessier and others in 1979. It is demonstrated that the metals bonded to other 3 species (carbonate, Fe-Mn oxide, and organic matter) except those bonded to the ex- changeable species in efficient speciation can be released under the Earth’s surface conditions, when pH=4 in the reaction system, and the higher correlation coefficient indicated that the concentrations of heavy metals released from soil into the solution vary approximately with reaction time in terms of index regulations.展开更多
Potassium （K） release characteristics in soil play a significant role in supplying available K. Information on K-release characteristics in soils of central Iran is limited. The objectives of this study were to dete...Potassium （K） release characteristics in soil play a significant role in supplying available K. Information on K-release characteristics in soils of central Iran is limited. The objectives of this study were to determine K release characteristics and correlations of K release rate constants with K extracted by different chemical methods in surface soils of ten calcareous soils of central Iran. The kinetics of K release in the soils was determined by successive extraction with 0.01 mol L-1 CaC12 in a period of 2-2017 h at 25±1℃. Soil K was extracted by distilled water, 0.5 mol L-1 MgNO3, 0.002 mol L-1 SrC12, 0.1 mol L-1 BaC12, 0.01 mol L-1 CaC12, 1 mol L-1 NaC1, 1 mol L-1 boiling HNO3, 1 mol L-1 NH4OAC, Mehlich 1, 0.002 mol L-1 SrC12 ＋ 0.05 mol L-1 citric acid, and ammonium bicarbonate-diethylenetriamine pentaacetic acid （AB-DTPA）. A plot of cumulative amounts of K released showed a discontinuity in slope at 168 h. Thus, two equations were applied to two segments of the total reaction time （2-168 and 168-2 017 h）. Cumulative amounts of K released ranged from 55 to 299 mg kg-1 in 2-168 h and from 44 to 119 mg kg-1 in 168-2 017 h. Release kinetics of K in the two time segments conformed fairly well to parabolic diffusion, simplified Elovich, and power function models. There was a wide variation in the K release rate constants. Increasingly higher average concentrations of soil K were extracted by distilled water, Mehlich 1, SrC12, CaC12, SrC12 ＋ citric acid, AB-DTPA, MgNO3, NaCI, NH4OAc, BaCI2, and HNO3. Potassium release rate constants were significantly correlated with K extracted. The results of this study showed that information obtained from mathematical modeling in two reaction time segments can help to estimate the K-supplying power of soils.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
It is the basic requirement of the synergetic exploitation of deep mineral resources and geothermal resources to arrange the heat transfer tube in filling body. The heat release performance of filling body directly im...It is the basic requirement of the synergetic exploitation of deep mineral resources and geothermal resources to arrange the heat transfer tube in filling body. The heat release performance of filling body directly impacts on the exploiting efficiency of geothermal energy. Based on heat transfer theory, a three-dimensional unsteady heat transfer model of filling body is established by using FLUENT simulation software. Taking the horizontal U-shaped buried pipe as research object, the variation of temperature field in filling body around buried pipe is analyzed during the heat release process of filling body;the initial temperature of filling body, the diameter of buried pipe, the inlet temperature and inlet velocity of heat transfer fluid influencing of coupling heat transfer, which exists between heat transfer fluid and surrounding filling body within a certain axial distance of buried tube, and influencing of temperature difference between inlet and outlet of heat transfer fluid and on heat transfer performance of filling body are also discussed. It not only lays a theoretical foundation for the synergetic exploitation of mineral resources and geothermal energy in deep mines, but also provides a reference basis for the arrangement of buried pipes in filling body as well as the selection of working conditions for heat transfer fluid.展开更多
The electrochemical corrosion of ductile pipes(DPs)in drinking water distribution systems(DWDS)has a crucial impact on cement-mortar lining(CML)failure and metal release,potentially leading to drinking water quality d...The electrochemical corrosion of ductile pipes(DPs)in drinking water distribution systems(DWDS)has a crucial impact on cement-mortar lining(CML)failure and metal release,potentially leading to drinking water quality deterioration and posing a risk to public health.An in-situ scanning vibrating electrode technique(SVET)with micron-scale resolution,microscopic scale detection and water quality analysis were used to investigate the corrosion behavior and metal release from DPs throughout the whole CML failure process.Metal pollutants release occurred at three different stages of CML failure process,and there are potential risks of water quality deterioration exceeding the maximum allowable levels set by national standards in the partial failure stage and lining peeling stage.Furthermore,the effects of water chemistry(Cl^(−),SO_(4)^(2−),NO_(3)−,and Ca^(2+))on corrosion scale growth and iron release activity,were investigated during the CML partial failure stage.Results showed that the CML failure process in DPs was accelerated by the autocatalysis of localized corrosion.Cl^(−)was found to damage the uncorroded metal surface,while SO_(4)^(2−)mainly dissolved the corrosion scale surface,increasing iron release.Both the oxidation of NO_(3)−and selective sedimentation of Ca2+were found to enhance the stability of corrosion scales and inhibit iron release.展开更多
Phase Change Material(PCM)-based cold energy storage system(CESS)can effectively utilize the peak and valley power resources to reduce the excessive dependence on the power grid.In this study,a PCM-based CESS was desi...Phase Change Material(PCM)-based cold energy storage system(CESS)can effectively utilize the peak and valley power resources to reduce the excessive dependence on the power grid.In this study,a PCM-based CESS was designed for cold storage applications.The optimal number of PCM plates was determined through numerical simulations to meet the required cold storage temperature and control time.Additionally,the air temperature field,flow field,and melting characteristics of the PCMplates during the cooling release process were analyzed.The effects of plate positioning and thickness on the cooling release performance were further investigated.The results indicated that when 64PCMplateswere used,the duration formaintaining temperatures below−18℃increased from0.6 h to approximately 16.94 h.During the cooling release process,the temperature field in the cold storage exhibited stratification,and the melting of the PCM plates was non-uniform.Placing the PCM plates at the top or within the interlayers without cargo above proved more effective,with their cooling release power being approximately twice that of the PCM plates placed in the interlayers with cargo above.Furthermore,reducing the thickness of the PCMplates from15 to 7.5mmresulted in a 3.6-h increase in the time below−18℃and a 4.5-h reduction in the time required to reach 80%liquid phase fraction.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
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
Naturally degradable capsule provides a platform for sustained fragrance release.However,practical challenges such as low encapsulation efficiency and difficulty in sustained release are still limited in using fragran...Naturally degradable capsule provides a platform for sustained fragrance release.However,practical challenges such as low encapsulation efficiency and difficulty in sustained release are still limited in using fragranceloaded capsules.In this work,the natural materials sodium alginate and gelatine are dissolved and act as the aqueous phase,lavender is dissolved in caprylic/capric triglyceride(GTCC)as the oil phase,and SiO_(2) nanoparticles with neutralwettability as a solid emulsifier to form O/W Pickering emulsions simultaneously.Finally,multi-core capsules are prepared using the drop injection method with emulsions as templates.The results show that the capsules have been successfully prepared with a spherical morphology and multi-core structure,and the encapsulation rate of multi-core capsules can reach up to 99.6%.In addition,the multi-core capsules possess desirable sustained release performance,the cumulative sustained release rate of fragrance at 25℃over 49 days is only 32.5%.It is attributed to the significant protection of multi-core structure,Pickering emulsion nanoparticle membranes,and hydrogel network shell for encapsulated fragrance.This study is designed to deliver a new strategy for using sustained-release technology with fragrance in food,cosmetics,textiles,and other fields.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
文摘Conventional locking/release mechanisms often face challenges in aircraft wing separation processes,such as excessive impact loads and insufficient synchronization.These may cause structural damage to the airframe or attitude instability,seriously compromising mission reliability.To address this engineering challenge,this paper proposes a multi-point low-impact locking/release mechanism based on the mobility model and energy conversion strategy.Through establishing a DOF constraint framework system,this paper systematically analyzes the energy transfer and conversion characteristics during the wing separation process,reveals the generation mechanism of impact loads,and conducts research on low-impact design based on energy conversion strategy.Building on this foundation,a single-point locking/release mechanism employing parallel trapezoidal key shaft structure was designed,which increases frictional contact time and reduces the energy release rate,thereby achieving low-impact characteristics.The mechanism's performance was validated through physical prototype development and systematic functional testing(including unlocking force,synchronization,and impact tests).Experimental results demonstrate:(1)Under 14 kN preload condition,the maximum unlocking force was only 92.54 N,showing a linear relationship with preload that satisfies the"strong-connection/weak-unlock"design requirement;(2)Wing separation was completed within 46 ms,with synchronization time difference among three separation mechanisms stably controlled within 12-14 ms,proving rapid and reliable operation;(3)The unlocking impact acceleration ranged between 26 and 73 g,below the 100 g design limit,confirming the effectiveness of the energy conversion strategy.The proposed low-impact locking/release mechanism design method based on energy conversion strategy resolves the traditional challenges of high impact and synchronization deficiencies.The synergistic optimization mechanism of"structural load reduction and performance improvement"provides a highly reliable technical solution for wing separable mechanisms while offering novel design insights for wing connection/separation systems engineering.
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AIM:To investigate the long-term outcomes in acute primary angle closure(APAC)patients treated with lens extraction(LE)surgery and to identify risk factors for glaucomatous optic neuropathy(GON).METHODS:In this longitudinal observational study,detailed medical histories of APAC patients and comprehensive ophthalmic examinations at final followup were collected.Logistic regression analysis was performed to identify predictors of blindness.Univariate and multivariate linear regression analyses were conducted to determine risk factors associated with visual outcomes.RESULTS:This study included 39 affected eyes of 31 subjects(26 females)with an average age of 74.1±8.0y.At 6.7±4.2y after APAC attack,2(5.7%)eyes had bestcorrected visual acuity(VA)worse than 3/60.Advanced glaucomatous visual field loss was observed in 15(39.5%)affected eyes and 5(25.0%)fellow eyes.Nine affected eyes(23.7%)had GON,and 11(28.9%)were blind.Six(15.4%)affected eyes and 2(9.1%)fellow eyes had suspicious progression.A significantly higher blindness rate in factory workers compared to office workers.Logistic regression identified that worse VA at attack(OR 10.568,95%CI 1.288-86.695;P=0.028)and worse early postoperative VA(OR 13.214,95%CI 1.157-150.881;P=0.038)were risk factors for blindness.Multivariate regression showed that longer duration of elevated intraocular pressure(P=0.004)and worse early postoperative VA(P=0.009)were associated with worse visual outcomes.CONCLUSION:Despite LE surgery,some APAC patients experience continued visual function deterioration.Lifelong monitoring is necessary.Target pressure and progression rates should be re-evaluated during follow-up.
文摘An acid sulfate soil sample was successively extracted with deionized water, 1 mol L-1 KCl and 0.000 5 mol L-l Ca(OH)2 solutions. The results showed that only very small amounts of acidity were extracted by deionized water, possibly through slow jarosite hydrolysis. Acid release through jarosite hydrolysis was greatly enhanced by Ca(OH)2 extraction at the expense of the added OH- being neutralized by the acid released. Successive extraction of the sample with KCl removed the largest amounts of acidity from the sample. However, it is likely that the major form of acidity released by KCl extraction was exchangeable acidity. The results also show the occurrence of low or non charged Al and Fe species in water and Ca(OH)2 extracts after first a few extractions. It appears that such a phenomenon was related to a decreasing EC value with increasing number of extractions.
文摘A simulating experiment was carried out on the interaction between natural precipitation and soil. The results demonstrated that the contents of heavy metals (V, Co, Cr, and Ni) released from soil into the solution under Earth’s surface conditions are higher than the contents of those metals bonded to exchangeable species, which were extracted by sequential extraction procedure recommended by Tessier and others in 1979. It is demonstrated that the metals bonded to other 3 species (carbonate, Fe-Mn oxide, and organic matter) except those bonded to the ex- changeable species in efficient speciation can be released under the Earth’s surface conditions, when pH=4 in the reaction system, and the higher correlation coefficient indicated that the concentrations of heavy metals released from soil into the solution vary approximately with reaction time in terms of index regulations.
文摘Potassium （K） release characteristics in soil play a significant role in supplying available K. Information on K-release characteristics in soils of central Iran is limited. The objectives of this study were to determine K release characteristics and correlations of K release rate constants with K extracted by different chemical methods in surface soils of ten calcareous soils of central Iran. The kinetics of K release in the soils was determined by successive extraction with 0.01 mol L-1 CaC12 in a period of 2-2017 h at 25±1℃. Soil K was extracted by distilled water, 0.5 mol L-1 MgNO3, 0.002 mol L-1 SrC12, 0.1 mol L-1 BaC12, 0.01 mol L-1 CaC12, 1 mol L-1 NaC1, 1 mol L-1 boiling HNO3, 1 mol L-1 NH4OAC, Mehlich 1, 0.002 mol L-1 SrC12 ＋ 0.05 mol L-1 citric acid, and ammonium bicarbonate-diethylenetriamine pentaacetic acid （AB-DTPA）. A plot of cumulative amounts of K released showed a discontinuity in slope at 168 h. Thus, two equations were applied to two segments of the total reaction time （2-168 and 168-2 017 h）. Cumulative amounts of K released ranged from 55 to 299 mg kg-1 in 2-168 h and from 44 to 119 mg kg-1 in 168-2 017 h. Release kinetics of K in the two time segments conformed fairly well to parabolic diffusion, simplified Elovich, and power function models. There was a wide variation in the K release rate constants. Increasingly higher average concentrations of soil K were extracted by distilled water, Mehlich 1, SrC12, CaC12, SrC12 ＋ citric acid, AB-DTPA, MgNO3, NaCI, NH4OAc, BaCI2, and HNO3. Potassium release rate constants were significantly correlated with K extracted. The results of this study showed that information obtained from mathematical modeling in two reaction time segments can help to estimate the K-supplying power of soils.
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Projects(51974225,51874229,51674188,51904224,51904225,51504182) supported by the National Natural Science Foundation of ChinaProjects(2018JM5161,2018JQ5183,2015JQ5187) supported by the Natural Science Basic Research Plan of Shaanxi,China
文摘It is the basic requirement of the synergetic exploitation of deep mineral resources and geothermal resources to arrange the heat transfer tube in filling body. The heat release performance of filling body directly impacts on the exploiting efficiency of geothermal energy. Based on heat transfer theory, a three-dimensional unsteady heat transfer model of filling body is established by using FLUENT simulation software. Taking the horizontal U-shaped buried pipe as research object, the variation of temperature field in filling body around buried pipe is analyzed during the heat release process of filling body;the initial temperature of filling body, the diameter of buried pipe, the inlet temperature and inlet velocity of heat transfer fluid influencing of coupling heat transfer, which exists between heat transfer fluid and surrounding filling body within a certain axial distance of buried tube, and influencing of temperature difference between inlet and outlet of heat transfer fluid and on heat transfer performance of filling body are also discussed. It not only lays a theoretical foundation for the synergetic exploitation of mineral resources and geothermal energy in deep mines, but also provides a reference basis for the arrangement of buried pipes in filling body as well as the selection of working conditions for heat transfer fluid.
基金supported by the National Natural Science Foundation of China(Nos.51808158,52170101,and 52200116)Tianjin Natural Science Foundation(No.23JCYBJC00640).
文摘The electrochemical corrosion of ductile pipes(DPs)in drinking water distribution systems(DWDS)has a crucial impact on cement-mortar lining(CML)failure and metal release,potentially leading to drinking water quality deterioration and posing a risk to public health.An in-situ scanning vibrating electrode technique(SVET)with micron-scale resolution,microscopic scale detection and water quality analysis were used to investigate the corrosion behavior and metal release from DPs throughout the whole CML failure process.Metal pollutants release occurred at three different stages of CML failure process,and there are potential risks of water quality deterioration exceeding the maximum allowable levels set by national standards in the partial failure stage and lining peeling stage.Furthermore,the effects of water chemistry(Cl^(−),SO_(4)^(2−),NO_(3)−,and Ca^(2+))on corrosion scale growth and iron release activity,were investigated during the CML partial failure stage.Results showed that the CML failure process in DPs was accelerated by the autocatalysis of localized corrosion.Cl^(−)was found to damage the uncorroded metal surface,while SO_(4)^(2−)mainly dissolved the corrosion scale surface,increasing iron release.Both the oxidation of NO_(3)−and selective sedimentation of Ca2+were found to enhance the stability of corrosion scales and inhibit iron release.
基金supported by National Natural Science Foundation of China(Nos.51806092,52201410)Non-Carbon Energy Conversion and Utilization Institute under the Shanghai Class IV Peak Disciplinary Development Program,High-End Foreign Experts Recruitment Plan of China(G2022013028L).
文摘Phase Change Material(PCM)-based cold energy storage system(CESS)can effectively utilize the peak and valley power resources to reduce the excessive dependence on the power grid.In this study,a PCM-based CESS was designed for cold storage applications.The optimal number of PCM plates was determined through numerical simulations to meet the required cold storage temperature and control time.Additionally,the air temperature field,flow field,and melting characteristics of the PCMplates during the cooling release process were analyzed.The effects of plate positioning and thickness on the cooling release performance were further investigated.The results indicated that when 64PCMplateswere used,the duration formaintaining temperatures below−18℃increased from0.6 h to approximately 16.94 h.During the cooling release process,the temperature field in the cold storage exhibited stratification,and the melting of the PCM plates was non-uniform.Placing the PCM plates at the top or within the interlayers without cargo above proved more effective,with their cooling release power being approximately twice that of the PCM plates placed in the interlayers with cargo above.Furthermore,reducing the thickness of the PCMplates from15 to 7.5mmresulted in a 3.6-h increase in the time below−18℃and a 4.5-h reduction in the time required to reach 80%liquid phase fraction.
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.
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Naturally degradable capsule provides a platform for sustained fragrance release.However,practical challenges such as low encapsulation efficiency and difficulty in sustained release are still limited in using fragranceloaded capsules.In this work,the natural materials sodium alginate and gelatine are dissolved and act as the aqueous phase,lavender is dissolved in caprylic/capric triglyceride(GTCC)as the oil phase,and SiO_(2) nanoparticles with neutralwettability as a solid emulsifier to form O/W Pickering emulsions simultaneously.Finally,multi-core capsules are prepared using the drop injection method with emulsions as templates.The results show that the capsules have been successfully prepared with a spherical morphology and multi-core structure,and the encapsulation rate of multi-core capsules can reach up to 99.6%.In addition,the multi-core capsules possess desirable sustained release performance,the cumulative sustained release rate of fragrance at 25℃over 49 days is only 32.5%.It is attributed to the significant protection of multi-core structure,Pickering emulsion nanoparticle membranes,and hydrogel network shell for encapsulated fragrance.This study is designed to deliver a new strategy for using sustained-release technology with fragrance in food,cosmetics,textiles,and other fields.
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.
