The extraction behavior of rare earths was studied by using paraffin with ceresin as a diluent containing 1-phenyl-3-methyl-4-benzoyl-pyrazolone-5.In solid phase,the composition of complexes is REP_3.The equilib- rium...The extraction behavior of rare earths was studied by using paraffin with ceresin as a diluent containing 1-phenyl-3-methyl-4-benzoyl-pyrazolone-5.In solid phase,the composition of complexes is REP_3.The equilib- rium extraction constants and pH_(1/2) values of solid-liquid extraction are higher than those of normal liquid-liquid extraction.The extraction efficiency tends to maximum when the ratio of phases is 1:1.When the extraction temperature is higher than the melting point of paraffin and the extraction time is over 10 min,the extraction efficiency keeps constant.Moreover,the relationship among separation factor,equilibrium extrac- tion constant,pH_(1/2) value and atomic number was obtained.The mechanism of solid-liquid extraction is analogous to that of liquid-liquid extraction.展开更多
Solid liquid extraction of copper ion (I) with 2, 9-dimethyl-1, 10-phenanthroline (neo-cuproine, DMP) into molten naphthalene followed by chloroform spectrophotometric determination has been studied experimentally. Th...Solid liquid extraction of copper ion (I) with 2, 9-dimethyl-1, 10-phenanthroline (neo-cuproine, DMP) into molten naphthalene followed by chloroform spectrophotometric determination has been studied experimentally. The ternary complex Cu(I)-DMP-ClO4 was extracted quantitatively into molten naphthalene in the range of pH from 5 to 6 at 85 C-. Absorbance was spectrophotometrically determined at 459 nm against the reagent blank after the solid naphthalene layer was anhydrously dissolved in chloroform. Beer's law is obeyed over a concentration range of 0.5-70 mug/mL. The molar absorptivity and Sandell's sensitivity are 1.0x10(4) L/(mol(.)cm) and 0.0099 mug(.)cm(2) respectively. In addition, the various conditions on determination and the interference of coexisted ions were discussed, and the method was applied to the determination of copper ion both in tea samples and cadmium sulfate reagents. The results are in good agreement with those obtained by ICP AES method.展开更多
The recovery of yttrium is proposed by applying a solid-liquid extraction process using di-2-ethyl hexylphosphoric acid(D2EHPA) as extracting agent.The extracting agents were supported on a macro porous polymeric resi...The recovery of yttrium is proposed by applying a solid-liquid extraction process using di-2-ethyl hexylphosphoric acid(D2EHPA) as extracting agent.The extracting agents were supported on a macro porous polymeric resin XAD-7(solid phase).Yttrium ions extraction and discharge tests were performed,firstly from a synthetic aqueous solution of 100 mg/L Y(liquid phase) at 25℃ with stirring.The effects of pH of aqueous solutions bearing yttrium,volume fraction of extracting agents and the solid/liquid(S/L)ratio on the yttrium recovery were studied.The most favorable conditions for yttrium ions extraction are;20 vol% D_(2)EHPA functionalized resin,pH=1.5 and an S/L ratio of 10 mg/mL The discharge of yttrium ions was done under the same conditions of extraction stage,using a 2 mol/L [H_(2)SO_(4)] as stripping solution.Up to 80% yttrium is extracted,while 75% yttrium is recovered in the striping solution.In all experiments,the reaction equilibrium is reached after 20 min,and the kinetics for the extraction stage was determined as a second-order model.Also,experiments were carried out to discharge the yttriumloaded resins,and it has been determined that the best pH value to strip the Y ions is 1.5.Cyclic tests of extraction and discharge for yttrium ions show that the functionalized resin can work at least five cycles without decreasing its efficiency.Finally,the proposed process was tested in a real solution with Y ions fro m a waste fluorescent la mp powder leached in H_(2)SO_(4),demonstrating the ability to effectively recover yttrium,separating it from various metals from the studied residue.展开更多
Silver nanoparticles were synthesized in reverse micelles consisting of sucrose fatty acid esters by dissolving reactant powder in the water pool of reverse micelles through the solid-liquid extraction. Silver nanopar...Silver nanoparticles were synthesized in reverse micelles consisting of sucrose fatty acid esters by dissolving reactant powder in the water pool of reverse micelles through the solid-liquid extraction. Silver nanoparticles having various sizes and shapes were obtained at high concentration. The size of silver nanoparticles was controlled by reaction temperature. Moreover, the size of silver nanoparticles was dependent upon the average esterification degree of sucrose fatty acid esters forming reverse micelles. The wavelength in the peaks, which corresponded upon the localized surface plasmon resonance of resultant silver nanoparticles, was correlated with their sizes.展开更多
The latest development in solid-liquid extraction resin for the separation of REE was reviewed. The chemistry of inorganic supports based on diatomite, silica gel or alumina as well as organic supports based on cellul...The latest development in solid-liquid extraction resin for the separation of REE was reviewed. The chemistry of inorganic supports based on diatomite, silica gel or alumina as well as organic supports based on cellulose, chitosan natural macromolecular support and poly(styrene-divinylbenzene), polyacrylate, aldehyde polymer, polyurethane, polyacrylonitrile synthetic macromolecular supports was covered, low molecular weight extractants such as acidic, organophosphorus, amine, macrocyclic compounds as well as macromolecular extractants were outlined. The different approaches involving ion exchange, ion-pair and chelating separation mechanisms were discussed. Physical adsorption, enclosing and chemical bonding mechanisms about extractants immobilized on solid supports were presented. The relation between resin shape and the property of packed columns was highlighted. Modern synthetic techniques such as molecular assembly, ionic imprinting, chemical modification for the preparation of resins were described. Basic fundamentals, advantages and synthetic methods of novel solid-liquid extraction resins as well as possibilities to improve resins performance were introduced.展开更多
An effective Spectrophotometric determination of platinum withl-(2-pyridylazo)-2-naphthol (PAN) using molten naphthalene as a diluent was studied. A green complexof platinum with PAN is formed at 90℃. In the range of...An effective Spectrophotometric determination of platinum withl-(2-pyridylazo)-2-naphthol (PAN) using molten naphthalene as a diluent was studied. A green complexof platinum with PAN is formed at 90℃. In the range of pH 2.5-6.5, the complex is quantitativelyextracted into molten naphthalene. The organic phase is anhydrously dissolved in CHCl_3 to hedetermined spectrophotometrically at 690 nm against the reagent blank. Beer's law is obeyed over theconcentration range of 0.5-5.0 μg/μL. The molar absorptivity and Sandell's sensitivity are 1.6 x10^5 L·mol^(-1)·cm^(-1) and 0.0048 mg·cm^(-2), respectively. The optimum conditions fordetermination are obtained. The interferences of various ions are observed in detail. The method hasbeen applied to the determination of platinum in synthetic samples.展开更多
The extraction behavior of Sm(III), Eu(III),Er(III) and Yb(III) with 1- nitroso -2-naphthol (HA) in paraffin has been studied. The composition of,extracted complexes has been determined to be LnA(3) by slope analysis ...The extraction behavior of Sm(III), Eu(III),Er(III) and Yb(III) with 1- nitroso -2-naphthol (HA) in paraffin has been studied. The composition of,extracted complexes has been determined to be LnA(3) by slope analysis method. The effect of temperature on extraction system is also investigated and thermodynamic parameters are obtained.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 overview of extraction of some trace metal ions using molten solvent (lowmelting substance) during last two decades is presented. The development of this technique since itsinception is briefly traced. The comparis...An overview of extraction of some trace metal ions using molten solvent (lowmelting substance) during last two decades is presented. The development of this technique since itsinception is briefly traced. The comparison of extraction efficiency, thermodynamics and kineticsmainly involving extraction of rare earth ions between molten solvent extraction at high temperatureand usual liquid-liquid extraction at room temperature are discussed in detail. The variousparameters obtained from the previous and present studies such as equilibrium extraction constantK_(ex), pH_(1/2), thermodynamic and kinetic data are displayed in tabular form. Finally, the currentdemands, disadvantages and future prospects are also evaluated.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 current work concerns the optimization process of phenolic compounds solid liquid extraction from grape byproducts at high temperatures and short incubation times. The effect of five experimental parameters (solid...The current work concerns the optimization process of phenolic compounds solid liquid extraction from grape byproducts at high temperatures and short incubation times. The effect of five experimental parameters (solidliquid ratio, particle size, time, temperature and solvent mixture) mostly believed to affect the extraction process was undertaken. A first response surface methodology experimental design was used to optimize the solid-liquid ratio and milling time parameters. A second design was used for the optimization of the quantitative and qualitative parameters. The quantitative parameters studied are: total phenolic compounds, flavonoid content, total monomeric anthocyanin composition and tannin concentration. The qualitative parameters analyzed are: antiradical activity and antioxidant capacity. The second design was based on the use of time, temperature and solvent mixture as optimization parameters. The assays were first conducted separately revealing the best experimental conditions for the maximization of each response variable alone. A simultaneous response surface methodology of all the responses taken together was then conducted, showing the optimal extraction conditions to be: 93 minutes at 94?C and in 66% ethanol/water solvent. The maximal response values obtained for each parameter are: Total Phenolic Compounds yield (5.5 g GAE/100g DM), Flavonoid Content (5.4 g GAE/100g DM), Total Monomeric Anthocyanin yield (70.3 mg/100g DM), Tannin Concentration (12.3 g/L), Antiradical Activity (67.3%) and Total Antioxidant Capacity (393 mgAAE/L). All of the optimal values were acquired at 3 mL/g solid-liquid ratio and 6.8 min milling time. The obtained extracts could be used as natural bioactive compounds in several industrial applications.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
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The extraction behavior of rare earths was studied by using paraffin with ceresin as a diluent containing 1-phenyl-3-methyl-4-benzoyl-pyrazolone-5.In solid phase,the composition of complexes is REP_3.The equilib- rium extraction constants and pH_(1/2) values of solid-liquid extraction are higher than those of normal liquid-liquid extraction.The extraction efficiency tends to maximum when the ratio of phases is 1:1.When the extraction temperature is higher than the melting point of paraffin and the extraction time is over 10 min,the extraction efficiency keeps constant.Moreover,the relationship among separation factor,equilibrium extrac- tion constant,pH_(1/2) value and atomic number was obtained.The mechanism of solid-liquid extraction is analogous to that of liquid-liquid extraction.
基金This research was financially supported by the project KJCXGC-01 of Northwest Normal University, China.
文摘Solid liquid extraction of copper ion (I) with 2, 9-dimethyl-1, 10-phenanthroline (neo-cuproine, DMP) into molten naphthalene followed by chloroform spectrophotometric determination has been studied experimentally. The ternary complex Cu(I)-DMP-ClO4 was extracted quantitatively into molten naphthalene in the range of pH from 5 to 6 at 85 C-. Absorbance was spectrophotometrically determined at 459 nm against the reagent blank after the solid naphthalene layer was anhydrously dissolved in chloroform. Beer's law is obeyed over a concentration range of 0.5-70 mug/mL. The molar absorptivity and Sandell's sensitivity are 1.0x10(4) L/(mol(.)cm) and 0.0099 mug(.)cm(2) respectively. In addition, the various conditions on determination and the interference of coexisted ions were discussed, and the method was applied to the determination of copper ion both in tea samples and cadmium sulfate reagents. The results are in good agreement with those obtained by ICP AES method.
基金Project supported by Secretariat of Research and Postgraduate Studies National Polytechnic Institute (20221369 and 20231939)Consejo Nacional de Ciencia y Tecnologia CONACyT。
文摘The recovery of yttrium is proposed by applying a solid-liquid extraction process using di-2-ethyl hexylphosphoric acid(D2EHPA) as extracting agent.The extracting agents were supported on a macro porous polymeric resin XAD-7(solid phase).Yttrium ions extraction and discharge tests were performed,firstly from a synthetic aqueous solution of 100 mg/L Y(liquid phase) at 25℃ with stirring.The effects of pH of aqueous solutions bearing yttrium,volume fraction of extracting agents and the solid/liquid(S/L)ratio on the yttrium recovery were studied.The most favorable conditions for yttrium ions extraction are;20 vol% D_(2)EHPA functionalized resin,pH=1.5 and an S/L ratio of 10 mg/mL The discharge of yttrium ions was done under the same conditions of extraction stage,using a 2 mol/L [H_(2)SO_(4)] as stripping solution.Up to 80% yttrium is extracted,while 75% yttrium is recovered in the striping solution.In all experiments,the reaction equilibrium is reached after 20 min,and the kinetics for the extraction stage was determined as a second-order model.Also,experiments were carried out to discharge the yttriumloaded resins,and it has been determined that the best pH value to strip the Y ions is 1.5.Cyclic tests of extraction and discharge for yttrium ions show that the functionalized resin can work at least five cycles without decreasing its efficiency.Finally,the proposed process was tested in a real solution with Y ions fro m a waste fluorescent la mp powder leached in H_(2)SO_(4),demonstrating the ability to effectively recover yttrium,separating it from various metals from the studied residue.
文摘Silver nanoparticles were synthesized in reverse micelles consisting of sucrose fatty acid esters by dissolving reactant powder in the water pool of reverse micelles through the solid-liquid extraction. Silver nanoparticles having various sizes and shapes were obtained at high concentration. The size of silver nanoparticles was controlled by reaction temperature. Moreover, the size of silver nanoparticles was dependent upon the average esterification degree of sucrose fatty acid esters forming reverse micelles. The wavelength in the peaks, which corresponded upon the localized surface plasmon resonance of resultant silver nanoparticles, was correlated with their sizes.
文摘The latest development in solid-liquid extraction resin for the separation of REE was reviewed. The chemistry of inorganic supports based on diatomite, silica gel or alumina as well as organic supports based on cellulose, chitosan natural macromolecular support and poly(styrene-divinylbenzene), polyacrylate, aldehyde polymer, polyurethane, polyacrylonitrile synthetic macromolecular supports was covered, low molecular weight extractants such as acidic, organophosphorus, amine, macrocyclic compounds as well as macromolecular extractants were outlined. The different approaches involving ion exchange, ion-pair and chelating separation mechanisms were discussed. Physical adsorption, enclosing and chemical bonding mechanisms about extractants immobilized on solid supports were presented. The relation between resin shape and the property of packed columns was highlighted. Modern synthetic techniques such as molecular assembly, ionic imprinting, chemical modification for the preparation of resins were described. Basic fundamentals, advantages and synthetic methods of novel solid-liquid extraction resins as well as possibilities to improve resins performance were introduced.
基金This work is financially supported by the Natural Science Foundation of Longdong University (No. SZZK0202)
文摘An effective Spectrophotometric determination of platinum withl-(2-pyridylazo)-2-naphthol (PAN) using molten naphthalene as a diluent was studied. A green complexof platinum with PAN is formed at 90℃. In the range of pH 2.5-6.5, the complex is quantitativelyextracted into molten naphthalene. The organic phase is anhydrously dissolved in CHCl_3 to hedetermined spectrophotometrically at 690 nm against the reagent blank. Beer's law is obeyed over theconcentration range of 0.5-5.0 μg/μL. The molar absorptivity and Sandell's sensitivity are 1.6 x10^5 L·mol^(-1)·cm^(-1) and 0.0048 mg·cm^(-2), respectively. The optimum conditions fordetermination are obtained. The interferences of various ions are observed in detail. The method hasbeen applied to the determination of platinum in synthetic samples.
文摘The extraction behavior of Sm(III), Eu(III),Er(III) and Yb(III) with 1- nitroso -2-naphthol (HA) in paraffin has been studied. The composition of,extracted complexes has been determined to be LnA(3) by slope analysis method. The effect of temperature on extraction system is also investigated and thermodynamic parameters are obtained.
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.
基金This work was financially supported by the Project of KJCXGC-01 of Northwest Normal University,and the Gansu Province Nature Science Foundation(ZR96016).]
文摘An overview of extraction of some trace metal ions using molten solvent (lowmelting substance) during last two decades is presented. The development of this technique since itsinception is briefly traced. The comparison of extraction efficiency, thermodynamics and kineticsmainly involving extraction of rare earth ions between molten solvent extraction at high temperatureand usual liquid-liquid extraction at room temperature are discussed in detail. The variousparameters obtained from the previous and present studies such as equilibrium extraction constantK_(ex), pH_(1/2), thermodynamic and kinetic data are displayed in tabular form. Finally, the currentdemands, disadvantages and future prospects are also evaluated.
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.
文摘The current work concerns the optimization process of phenolic compounds solid liquid extraction from grape byproducts at high temperatures and short incubation times. The effect of five experimental parameters (solidliquid ratio, particle size, time, temperature and solvent mixture) mostly believed to affect the extraction process was undertaken. A first response surface methodology experimental design was used to optimize the solid-liquid ratio and milling time parameters. A second design was used for the optimization of the quantitative and qualitative parameters. The quantitative parameters studied are: total phenolic compounds, flavonoid content, total monomeric anthocyanin composition and tannin concentration. The qualitative parameters analyzed are: antiradical activity and antioxidant capacity. The second design was based on the use of time, temperature and solvent mixture as optimization parameters. The assays were first conducted separately revealing the best experimental conditions for the maximization of each response variable alone. A simultaneous response surface methodology of all the responses taken together was then conducted, showing the optimal extraction conditions to be: 93 minutes at 94?C and in 66% ethanol/water solvent. The maximal response values obtained for each parameter are: Total Phenolic Compounds yield (5.5 g GAE/100g DM), Flavonoid Content (5.4 g GAE/100g DM), Total Monomeric Anthocyanin yield (70.3 mg/100g DM), Tannin Concentration (12.3 g/L), Antiradical Activity (67.3%) and Total Antioxidant Capacity (393 mgAAE/L). All of the optimal values were acquired at 3 mL/g solid-liquid ratio and 6.8 min milling time. The obtained extracts could be used as natural bioactive compounds in several industrial applications.
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.
