In response to the challenges in highway pavement distress detection,such as multiple defect categories,difficulties in feature extraction for different damage types,and slow identification speeds,this paper proposes ...In response to the challenges in highway pavement distress detection,such as multiple defect categories,difficulties in feature extraction for different damage types,and slow identification speeds,this paper proposes an enhanced pavement crack detection model named Star-YOLO11.This improved algorithm modifies the YOLO11 architecture by substituting the original C3k2 backbone network with a Star-s50 feature extraction network.The enhanced structure adjusts the number of stacked layers in the StarBlock module to optimize detection accuracy and improve model efficiency.To enhance the accuracy of pavement crack detection and improve model efficiency,three key modifications to the YOLO11 architecture are proposed.Firstly,the original C3k2 backbone is replaced with a StarBlock-based structure,forming the Star-s50 feature extraction backbone network.This lightweight redesign reduces computational complexity while maintaining detection precision.Secondly,to address the inefficiency of the original Partial Self-attention(PSA)mechanism in capturing localized crack features,the convolutional prior-aware Channel Prior Convolutional Attention(CPCA)mechanism is integrated into the channel dimension,creating a hybrid CPC-C2PSA attention structure.Thirdly,the original neck structure is upgraded to a Star Multi-Branch Auxiliary Feature Pyramid Network(SMAFPN)based on the Multi-Branch Auxiliary Feature Pyramid Network architecture,which adaptively fuses high-level semantic and low-level spatial information through Star-s50 connections and C3k2 extraction blocks.Additionally,a composite dataset augmentation strategy combining traditional and advanced augmentation techniques is developed.This strategy is validated on a specialized pavement dataset containing five distinct crack categories for comprehensive training and evaluation.Experimental results indicate that the proposed Star-YOLO11 achieves an accuracy of 89.9%(3.5%higher than the baseline),a mean average precision(mAP)of 90.3%(+2.6%),and an F1-score of 85.8%(+0.5%),while reducing the model size by 18.8%and reaching a frame rate of 225.73 frames per second(FPS)for real-time detection.It shows potential for lightweight deployment in pavement crack detection tasks.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
Background:Neurological disorders(NDs),including ischemic stroke(IS),Parkinson’s disease(PD),and Alzheimer’s disease(AD),are major contributors to global morbidity and mortality.Boswellia extract has demonstrated ne...Background:Neurological disorders(NDs),including ischemic stroke(IS),Parkinson’s disease(PD),and Alzheimer’s disease(AD),are major contributors to global morbidity and mortality.Boswellia extract has demonstrated neuroprotective properties,yet a comprehensive systematic review assessing its efficacy remains absent.This study aims to evaluate the efficacy of Boswellia extract in treating NDs,with a particular focus on its effects in AD and its potential for long-term neurorestoration,thereby supporting further investigation into Boswellia’s therapeutic role in ND management.Methods:A systematic literature search was performed in PubMed,Web of Science,ScienceDirect,and Google Scholar for English-language studies published up to March 2024.Eighteen studies met the inclusion criteria and were included in the meta-analysis.The study protocol was registered on PROSPERO(CRD42024524386).Eligible studies involved rodent models of IS,PD,or AD with post-operative interventions using Boswellia extract.Data extraction focused on mechanisms of action,dosages,treatment durations,and therapeutic outcomes.Studies were excluded if they involved non-ND models,combined treatments,or had incomplete data.Two researchers independently conducted literature screening and data extraction.Statistical analyses were conducted using Stata(version 17)and RevMan(version 5.4),employing fixed or random-effects models based on heterogeneity assessments.Result s:Boswellia extract significantly improved the mean effect size for NDs(ES=1.28,95%CI(1.05,1.51),P<0.001).Specifically,it reduced cerebral infarct volume in IS(SMD=−2.87,95%CI(−3.42,−2.32))and enhanced behavioral outcomes in AD(SMD=3.26,95%CI(2.07,5.14))and PD(SMD=5.37,95%CI(3.93,6.80)).Subgroup analyses revealed that Boswellia extract exhibited superior efficacy in AD when administered orally and via intra-cerebroventricular injection.Long-term treatment with Boswellia extract suggested potential neurorestorative effects.Additionally,Boswellia extract was more effective than its monomeric constituents,highlighting its promising role in ND treatment.Conclusion:Boswellia extract demonstrates significant neuroprotective effects across various NDs,particularly in AD and in promoting long-term neurorestoration.These findings support the need for further research into Boswellia’s potential as a therapeutic agent in the management of neurological disorders.展开更多
The increased interest in geothermal energy is evident,along with the exploitation of traditional hydrothermal systems,in the growing research and projects developing around the reuse of already-drilled oil,gas,and ex...The increased interest in geothermal energy is evident,along with the exploitation of traditional hydrothermal systems,in the growing research and projects developing around the reuse of already-drilled oil,gas,and exploration wells.The Republic of Croatia has around 4000 wells,however,due to a long period since most of these wells were drilled and completed,there is uncertainty about how many are available for retrofitting as deep-borehole heat exchangers.Nevertheless,as hydrocarbon production decreases,it is expected that the number of wells available for the revitalization and exploitation of geothermal energy will increase.The revitalization of wells via deep-borehole heat exchangers involves installing a coaxial heat exchanger and circulating the working fluid in a closed system,during which heat is transferred from the surrounding rock medium to the circulating fluid.Since drilled wells are not of uniformdepth and are located in areas with different thermal rock properties and geothermal gradients,an analysis was conducted to determine available thermal energy as a function of well depth,geothermal gradient,and circulating fluid flow rate.Additionally,an economic analysis was performed to determine the benefits of retrofitting existing assets,such as drilled wells,compared to drilling new wells to obtain the same amount of thermal energy.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
Optimizing the microchannel design of the next generation of chips requires an understanding of the in situ property evolution of the chip-based materials under fast cooling.This work overcomes the conventional relian...Optimizing the microchannel design of the next generation of chips requires an understanding of the in situ property evolution of the chip-based materials under fast cooling.This work overcomes the conventional reliance on reheating data of melt-quenched glasses by demonstrating direct observations of glass transition on cooling curves utilizing the most advanced fast differential scanning calorimetry.By leveraging an MEMS chip sensor that allows for rapid heat extraction from microgram-sized samples to a purged gas coolant,the device is able to reach ultra-fast cooling rates of up to 40,000 K·s^(−1).Four thermal regions are identified by examining the cooling behaviors of two metallic glasses.This is because the actual rate of the specimen can differ from the programmed rate,especially at high set rate when the actual rate decreases before the glass transition is completed.We define the operational window for reliable cooling curve analysis,build models with empirical and theoretical analyses to determine the maximum feasible cooling rate,and demonstrate how optimizing sample mass and environment temperature broaden this window.The method avoids deceptive structural relaxation effects verified by fictivetemperature analysis and permits the capture of full glass transition during cooling.展开更多
Parkinson’s disease(PD)is a debilitating neurological disorder affecting over 10 million people worldwide.PD classification models using voice signals as input are common in the literature.It is believed that using d...Parkinson’s disease(PD)is a debilitating neurological disorder affecting over 10 million people worldwide.PD classification models using voice signals as input are common in the literature.It is believed that using deep learning algorithms further enhances performance;nevertheless,it is challenging due to the nature of small-scale and imbalanced PD datasets.This paper proposed a convolutional neural network-based deep support vector machine(CNN-DSVM)to automate the feature extraction process using CNN and extend the conventional SVM to a DSVM for better classification performance in small-scale PD datasets.A customized kernel function reduces the impact of biased classification towards the majority class(healthy candidates in our consideration).An improved generative adversarial network(IGAN)was designed to generate additional training data to enhance the model’s performance.For performance evaluation,the proposed algorithm achieves a sensitivity of 97.6%and a specificity of 97.3%.The performance comparison is evaluated from five perspectives,including comparisons with different data generation algorithms,feature extraction techniques,kernel functions,and existing works.Results reveal the effectiveness of the IGAN algorithm,which improves the sensitivity and specificity by 4.05%–4.72%and 4.96%–5.86%,respectively;and the effectiveness of the CNN-DSVM algorithm,which improves the sensitivity by 1.24%–57.4%and specificity by 1.04%–163%and reduces biased detection towards the majority class.The ablation experiments confirm the effectiveness of individual components.Two future research directions have also been suggested.展开更多
Silver nanoparticles(Ag NPs)have attracted attention in the field of biomaterials due to their excellent antibacterial property.However,the reducing and stabilizing agents used for the chemical reduction of Ag NPs are...Silver nanoparticles(Ag NPs)have attracted attention in the field of biomaterials due to their excellent antibacterial property.However,the reducing and stabilizing agents used for the chemical reduction of Ag NPs are usually toxic and may cause water pollution.In this work,Ag NPs(31.2 nm in diameter)were prepared using the extract of straw,an agricultural waste,as the reducing and stabilizing agent.Experimental analysis revealed that the straw extract contained lignin,the structure of which possesses phenolic hydroxyl and methoxy groups that facilitate the reduction of silver salts into Ag NPs.The surfaces of Ag NPs were negatively charged due to the encapsulation of a thin layer of lignin molecules that prevented their aggregation.After the prepared Ag NPs were added to the precursor solution of acrylamide,free radical polymerization was triggered without the need for extra heating or light irradiation,resulting in the rapid formation of an Ag NP-polyacrylamide composite hydrogel.The inhibition zone test proved that the composite hydrogel possessed excellent antibacterial ability due to the presence of Ag NPs.The prepared hydrogel may have potential applications in the fabrication of biomedical materials,such as antibacterial dressings.展开更多
采用顶空固相微萃取(headspace solid-phase microextraction,HS-SPME)和液液萃取(liquid-liquid extraction,LLE)结合全二维气相色谱飞行时间质谱(comprehensive two-dimensional gas chromatography time of flight mass spectrometry...采用顶空固相微萃取(headspace solid-phase microextraction,HS-SPME)和液液萃取(liquid-liquid extraction,LLE)结合全二维气相色谱飞行时间质谱(comprehensive two-dimensional gas chromatography time of flight mass spectrometry,GC×GC-TOF-MS)以及香气活度值(odour active value,OAV),对红星二锅头白酒的挥发性成分进行全面解析。研究发现,HS-SPME、LLE分别定性出928、802种挥发性化合物,共计定性出1304种挥发性化合物,共同定性出426种挥发性化合物。基于HS-SPME数据,通过香气数据库筛选出具有香气特征的382种香气化合物,其中酯类相对百分含量占比最高,其次是醇类、酸类和醛类。计算得到了49种香气化合物OAV>1,其中酯类(辛酸乙酯、异戊酸乙酯等)和萜烯类(β-大马酮)对白酒风味的贡献最大,醛类(异戊醛、己醛等)和含硫类(二甲基三硫)其次,醇类(1-辛烯-3-醇)和含氮类(2,3,5-三甲基吡嗪)也有一定风味贡献。该研究丰富了红星二锅头白酒的风味研究,也为下一步生产研究及调控提供了理论和数据支撑。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 use of fresh versus frozen spermatozoa in men with nonobstructive azoospermia (NOA) undergoingin vitro fertilization (IVF)has been a debated hot topic among reproductive specialists. Each approach presents distinc...The use of fresh versus frozen spermatozoa in men with nonobstructive azoospermia (NOA) undergoingin vitro fertilization (IVF)has been a debated hot topic among reproductive specialists. Each approach presents distinct advantages and disadvantages,with fresh sperm typically showing superior sperm quality, while frozen sperm offers logistical flexibility and a reliable backup forrepeated cycles. This review summarizes the latest advancements in sperm retrieval and cryopreservation techniques, providingpractitioners with a comprehensive analysis of each option’s strengths and limitations. Comparative studies indicate that, althoughfresh sperm often has better quality metrics, cryopreservation methods such as vitrification have significantly improved postthawoutcomes, making frozen sperm a viable choice in assisted reproductive technologies (ART). The findings show comparablerates for fertilization, implantation, clinical pregnancy, and live birth between fresh and frozen microdissection testicular spermextraction (micro-TESE) sperm in many cases, although patient-specific factors such as timing, cost-effectiveness, and proceduralconvenience should guide the final decision. Ultimately, the choice of using fresh or frozen sperm should align with the individualneeds and conditions of patients. This tailored approach, supported by the latest advancements, can optimize ART outcomes andprovide personalized reproductive care.展开更多
In this study,eight different varieties of maize seeds were used as the research objects.Conduct 81 types of combined preprocessing on the original spectra.Through comparison,Savitzky-Golay(SG)-multivariate scattering...In this study,eight different varieties of maize seeds were used as the research objects.Conduct 81 types of combined preprocessing on the original spectra.Through comparison,Savitzky-Golay(SG)-multivariate scattering correction(MSC)-maximum-minimum normalization(MN)was identified as the optimal preprocessing technique.The competitive adaptive reweighted sampling(CARS),successive projections algorithm(SPA),and their combined methods were employed to extract feature wavelengths.Classification models based on back propagation(BP),support vector machine(SVM),random forest(RF),and partial least squares(PLS)were established using full-band data and feature wavelengths.Among all models,the(CARS-SPA)-BP model achieved the highest accuracy rate of 98.44%.This study offers novel insights and methodologies for the rapid and accurate identification of corn seeds as well as other crop seeds.展开更多
Objective Emerging evidence suggests that exposure to ultrafine particulate matter(UPM,aerodynamic diameter<0.1μm)is associated with adverse cardiovascular events.Previous studies have found that Shenlian(SL)extra...Objective Emerging evidence suggests that exposure to ultrafine particulate matter(UPM,aerodynamic diameter<0.1μm)is associated with adverse cardiovascular events.Previous studies have found that Shenlian(SL)extract possesses anti-inflammatory and antiapoptotic properties and has a promising protective effect at all stages of the atherosclerotic disease process.In this study,we aimed to investigated whether SL improves UPM-aggravated myocardial ischemic injury by inhibiting inflammation and cell apoptosis.Methods We established a mouse model of MI+UPM.Echocardiographic measurement,measurement of myocardialinfarct size,biochemical analysis,enzyme-linked immunosorbent assay(ELISA),histopathological analysis,Transferase dUTP Nick End Labeling(TUNEL),Western blotting(WB),Polymerase Chain Reaction(PCR)and so on were used to explore the anti-inflammatory and antiapoptotic effects of SL in vivo and in vitro.Results SL treatment can attenuate UPM-induced cardiac dysfunction by improving left ventricular ejection fraction,fractional shortening,and decreasing cardiac infarction area.SL significantly reduced the levels of myocardial enzymes and attenuated UPM-induced morphological alterations.Moreover,SL significantly reduced expression levels of the inflammatory cytokines IL-6,TNF-α,and MCP-1.UPM further increased the infiltration of macrophages in myocardial tissue,whereas SL intervention reversed this phenomenon.UPM also triggered myocardial apoptosis,which was markedly attenuated by SL treatment.The results of in vitro experiments revealed that SL prevented cell damage caused by exposure to UPM combined with hypoxia by reducing the expression of the inflammatory factor NF-κB and inhibiting apoptosis in H9c2 cells.Conclusion Overall,both in vivo and in vitro experiments demonstrated that SL attenuated UPMaggravated myocardial ischemic injury by inhibiting inflammation and cell apoptosis.The mechanisms were related to the downregulation of macrophages infiltrating heart tissues.展开更多
The therapeutic efficacy of traditional Chinese medicine has been widely acknowledged due to its extensive history of clinical effectiveness.However,the precise active components underlying each prescription remain in...The therapeutic efficacy of traditional Chinese medicine has been widely acknowledged due to its extensive history of clinical effectiveness.However,the precise active components underlying each prescription remain incompletely understood.Polysaccharides,as a major constituent of water decoctions—the most common preparation method for Chinese medicinals—may provide a crucial avenue for deepening our understanding of the efficacy principles of Chinese medicine and establishing a framework for its modern development.The structural complexity and diversity of Chinese herbal polysaccharides present significant challenges in their separation and analysis compared to small molecules.This paper aims to explore the potential of Chinese herbal polysaccharides efficiently by briefly summarizing recent advancements in polysaccharide chemical research,focusing on methods of acquisition,structure elucidation,and quality control.展开更多
The inhibitory properties of rapeseed cake meal extract(RCME)on the corrosion of cold rolled steel(CRS)in trichloroacetic acid(TCA)were systematically investigated using gravimetric,electrochemical,surface characteriz...The inhibitory properties of rapeseed cake meal extract(RCME)on the corrosion of cold rolled steel(CRS)in trichloroacetic acid(TCA)were systematically investigated using gravimetric,electrochemical,surface characterizations and theoretical calculations.The results demonstrate that RCME exhibits excellent inhibitory performance with a maximum inhibition efficiency of 92.7%for 100 mg L−1 RCME at 20℃.The adsorption of RCME obeys Langmuir isotherm at 20 and 30℃,Temkin isotherm at 40℃,and Freundlich isotherm at 50℃.RCME acts as a cathodic inhibitor.The charge transfer resistance is increased with the addition of RCME,while the double-layer capacitance decreases.SEM,AFM,CLSM,XPS,XRD and TOF-SIMS analyses confirm that the active components in RCME adsorb onto the surface of CRS,forming a protective film that effectively inhibits the corrosion of CRS by TCA.Along with the increase in the concentration of RCME,the surface tension of the inhibited solution gradually decreases,while the electrical conductivity increases before stabilizing.HPLC-MS and FTIR analyses reveal rutin,linolenic acid,linoleic acid and adenine are the effective substances in RCME.Quantum chemical(QC)calculations and molecular dynamic(MD)simulations indicate that the active centers of the effective inhibitor molecules are predominantly located on benzene rings,O-or N-containing heterocyclic rings,and functional groups such as C=O and C=C.Additionally,their main chains adsorb onto the Fe(001)surface in an approximately flat manner,involving both chemical and physical adsorption processes.展开更多
Anomaly Detection (AD) has been extensively adopted in industrial settings to facilitate quality control of products. It is critical to industrial production, especially to areas such as aircraft manufacturing, which ...Anomaly Detection (AD) has been extensively adopted in industrial settings to facilitate quality control of products. It is critical to industrial production, especially to areas such as aircraft manufacturing, which require strict part qualification rates. Although being more efficient and practical, few-shot AD has not been well explored. The existing AD methods only extract features in a single frequency while defects exist in multiple frequency domains. Moreover, current methods have not fully leveraged the few-shot support samples to extract input-related normal patterns. To address these issues, we propose an industrial few-shot AD method, Feature Extender for Anomaly Detection (FEAD), which extracts normal patterns in multiple frequency domains from few-shot samples under the guidance of the input sample. Firstly, to achieve better coverage of normal patterns in the input sample, we introduce a Sample-Conditioned Transformation Module (SCTM), which transforms support features under the guidance of the input sample to obtain extra normal patterns. Secondly, to effectively distinguish and localize anomaly patterns in multiple frequency domains, we devise an Adaptive Descriptor Construction Module (ADCM) to build and select pattern descriptors in a series of frequencies adaptively. Finally, an auxiliary task for SCTM is designed to ensure the diversity of transformations and include more normal patterns into support features. Extensive experiments on two widely used industrial AD datasets (MVTec-AD and VisA) demonstrate the effectiveness of the proposed FEAD.展开更多
As a typical bioflavonoid,diosmetin is desirable in the field of natural medicine,healthy food,and cosmetics by anti-cancer,antibacterial,antioxidant,estrogen-like and anti-inflammatory activities,and it comes from a ...As a typical bioflavonoid,diosmetin is desirable in the field of natural medicine,healthy food,and cosmetics by anti-cancer,antibacterial,antioxidant,estrogen-like and anti-inflammatory activities,and it comes from a wide range of sources in traditional Chinese medicine like spider fragrance,spearmint and chrysanthemum,as well as in Citrus fruit.However,traditional analytical methods such as silica gel column chromatography face multiple challenges in the selective extraction of diosmetin from biological materials and traditional Chinese medicinal materials.Therefore,it is urgent to develop a new type of absorbent with high efficiency,recyclability and good specificity to diosmetin.In this investigation,a magnetic surface molecularly imprinted polymer(labeled as Diosmetin/SMIPs)was synthesized employing magnetic nanoparticles as the carrier and 4-vinylpyridinyl(4-VP)as the functional monomer by surface imprinting technology.The functional monomer was screened by the binding energy(△E)between functional monomers and template molecules via computational simulation.The Diosmetin/SMIPs had a high level of specific recognition and adsorption capability towards diosmetin with a 20.25 mg g^(-1) adsorption capacity and an imprinting factor(IF)of 2.28.Additionally,it demonstrated excellent regeneration performance with 8 adsorption/desorption cycles.In addition,91.20%-94.16% of spiked diosmetin was recovered from the lemon peel samples.The strategy of constructing Diosmetin/SMIPs based on computational simulation can effectively enhance the specific adsorption performance of diosmetin.Meanwhile,Diosmetin/SMIPs synthesized by imprinting polymerization showed excellent anti-interference and reusability,and realized efficient targeted extraction of diosmetin from lemon peel samples.The results of this investigation provide a promising adsorbent for selective enrichment of diosmetin from Citrus fruit and complicated materials.展开更多
Identification of the most appropriate chemically extractable pool for evaluating Cd and Pb availability remains elusive,hindering accurate assessment on environmental risks and effectiveness of remediation strategies...Identification of the most appropriate chemically extractable pool for evaluating Cd and Pb availability remains elusive,hindering accurate assessment on environmental risks and effectiveness of remediation strategies.This study evaluated the feasibility of European Community Bureau of Reference(BCR)sequential extraction,Ca(NO_(3))_(2)extraction,and water extraction on assessing Cd and Pb availability in agricultural soil amended with slaked lime,magnesium hydroxide,corn stover biochar,and calcium dihydrogen phosphate.Moreover,the enriched isotope tracing technique(^(112)Cd and^(206)Pb)was employed to evaluate the aging process of newly introduced Cd and Pbwithin 56 days’incubation.Results demonstrated that extractable pools by BCR and Ca(NO_(3))_(2)extraction were little impacted by amendments and showed little correlation with soil pH.This is notable because soil pH is closely linked to metal availability,indicating these extraction methods may not adequately reflect metal availability.Conversely,water-soluble concentrations of Cd and Pb were markedly influenced by amendments and exhibited strong correlations with pH(Pearson’s r:-0.908 to-0.825,P<0.001),suggesting water extraction as a more sensitive approach.Furthermore,newly introduced metals underwent a more evident aging process as demonstrated by acid-soluble and water-soluble pools.Additionally,water-soluble concentrations of essential metals were impacted by soil amendments,raising caution on their potential effects on plant growth.These findings suggest water extraction as a promising and attractive method to evaluate Cd and Pb availability,which will help provide assessment guidance for environmental risks caused by heavy metals and develop efficient remediation strategies.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
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
基金funded by the Jiangxi SASAC Science and Technology Innovation Special Project and the Key Technology Research and Application Promotion of Highway Overload Digital Solution.
文摘In response to the challenges in highway pavement distress detection,such as multiple defect categories,difficulties in feature extraction for different damage types,and slow identification speeds,this paper proposes an enhanced pavement crack detection model named Star-YOLO11.This improved algorithm modifies the YOLO11 architecture by substituting the original C3k2 backbone network with a Star-s50 feature extraction network.The enhanced structure adjusts the number of stacked layers in the StarBlock module to optimize detection accuracy and improve model efficiency.To enhance the accuracy of pavement crack detection and improve model efficiency,three key modifications to the YOLO11 architecture are proposed.Firstly,the original C3k2 backbone is replaced with a StarBlock-based structure,forming the Star-s50 feature extraction backbone network.This lightweight redesign reduces computational complexity while maintaining detection precision.Secondly,to address the inefficiency of the original Partial Self-attention(PSA)mechanism in capturing localized crack features,the convolutional prior-aware Channel Prior Convolutional Attention(CPCA)mechanism is integrated into the channel dimension,creating a hybrid CPC-C2PSA attention structure.Thirdly,the original neck structure is upgraded to a Star Multi-Branch Auxiliary Feature Pyramid Network(SMAFPN)based on the Multi-Branch Auxiliary Feature Pyramid Network architecture,which adaptively fuses high-level semantic and low-level spatial information through Star-s50 connections and C3k2 extraction blocks.Additionally,a composite dataset augmentation strategy combining traditional and advanced augmentation techniques is developed.This strategy is validated on a specialized pavement dataset containing five distinct crack categories for comprehensive training and evaluation.Experimental results indicate that the proposed Star-YOLO11 achieves an accuracy of 89.9%(3.5%higher than the baseline),a mean average precision(mAP)of 90.3%(+2.6%),and an F1-score of 85.8%(+0.5%),while reducing the model size by 18.8%and reaching a frame rate of 225.73 frames per second(FPS)for real-time detection.It shows potential for lightweight deployment in pavement crack detection tasks.
文摘Since Google introduced the concept of Knowledge Graphs(KGs)in 2012,their construction technologies have evolved into a comprehensive methodological framework encompassing knowledge acquisition,extraction,representation,modeling,fusion,computation,and storage.Within this framework,knowledge extraction,as the core component,directly determines KG quality.In military domains,traditional manual curation models face efficiency constraints due to data fragmentation,complex knowledge architectures,and confidentiality protocols.Meanwhile,crowdsourced ontology construction approaches from general domains prove non-transferable,while human-crafted ontologies struggle with generalization deficiencies.To address these challenges,this study proposes an OntologyAware LLM Methodology for Military Domain Knowledge Extraction(LLM-KE).This approach leverages the deep semantic comprehension capabilities of Large Language Models(LLMs)to simulate human experts’cognitive processes in crowdsourced ontology construction,enabling automated extraction of military textual knowledge.It concurrently enhances knowledge processing efficiency and improves KG completeness.Empirical analysis demonstrates that this method effectively resolves scalability and dynamic adaptation challenges in military KG construction,establishing a novel technological pathway for advancing military intelligence development.
基金supported by the National Natural Science Foundation of China,specifically through grants(No.8227431382304947)Key Research and Development Project of Shaanxi Province(2023GHZD43).Peer re v iew information。
文摘Background:Neurological disorders(NDs),including ischemic stroke(IS),Parkinson’s disease(PD),and Alzheimer’s disease(AD),are major contributors to global morbidity and mortality.Boswellia extract has demonstrated neuroprotective properties,yet a comprehensive systematic review assessing its efficacy remains absent.This study aims to evaluate the efficacy of Boswellia extract in treating NDs,with a particular focus on its effects in AD and its potential for long-term neurorestoration,thereby supporting further investigation into Boswellia’s therapeutic role in ND management.Methods:A systematic literature search was performed in PubMed,Web of Science,ScienceDirect,and Google Scholar for English-language studies published up to March 2024.Eighteen studies met the inclusion criteria and were included in the meta-analysis.The study protocol was registered on PROSPERO(CRD42024524386).Eligible studies involved rodent models of IS,PD,or AD with post-operative interventions using Boswellia extract.Data extraction focused on mechanisms of action,dosages,treatment durations,and therapeutic outcomes.Studies were excluded if they involved non-ND models,combined treatments,or had incomplete data.Two researchers independently conducted literature screening and data extraction.Statistical analyses were conducted using Stata(version 17)and RevMan(version 5.4),employing fixed or random-effects models based on heterogeneity assessments.Result s:Boswellia extract significantly improved the mean effect size for NDs(ES=1.28,95%CI(1.05,1.51),P<0.001).Specifically,it reduced cerebral infarct volume in IS(SMD=−2.87,95%CI(−3.42,−2.32))and enhanced behavioral outcomes in AD(SMD=3.26,95%CI(2.07,5.14))and PD(SMD=5.37,95%CI(3.93,6.80)).Subgroup analyses revealed that Boswellia extract exhibited superior efficacy in AD when administered orally and via intra-cerebroventricular injection.Long-term treatment with Boswellia extract suggested potential neurorestorative effects.Additionally,Boswellia extract was more effective than its monomeric constituents,highlighting its promising role in ND treatment.Conclusion:Boswellia extract demonstrates significant neuroprotective effects across various NDs,particularly in AD and in promoting long-term neurorestoration.These findings support the need for further research into Boswellia’s potential as a therapeutic agent in the management of neurological disorders.
文摘The increased interest in geothermal energy is evident,along with the exploitation of traditional hydrothermal systems,in the growing research and projects developing around the reuse of already-drilled oil,gas,and exploration wells.The Republic of Croatia has around 4000 wells,however,due to a long period since most of these wells were drilled and completed,there is uncertainty about how many are available for retrofitting as deep-borehole heat exchangers.Nevertheless,as hydrocarbon production decreases,it is expected that the number of wells available for the revitalization and exploitation of geothermal energy will increase.The revitalization of wells via deep-borehole heat exchangers involves installing a coaxial heat exchanger and circulating the working fluid in a closed system,during which heat is transferred from the surrounding rock medium to the circulating fluid.Since drilled wells are not of uniformdepth and are located in areas with different thermal rock properties and geothermal gradients,an analysis was conducted to determine available thermal energy as a function of well depth,geothermal gradient,and circulating fluid flow rate.Additionally,an economic analysis was performed to determine the benefits of retrofitting existing assets,such as drilled wells,compared to drilling new wells to obtain the same amount of thermal energy.
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supported by the National Natural Science Foundation of China (Grant Nos.92580120 and 52471188)。
文摘Optimizing the microchannel design of the next generation of chips requires an understanding of the in situ property evolution of the chip-based materials under fast cooling.This work overcomes the conventional reliance on reheating data of melt-quenched glasses by demonstrating direct observations of glass transition on cooling curves utilizing the most advanced fast differential scanning calorimetry.By leveraging an MEMS chip sensor that allows for rapid heat extraction from microgram-sized samples to a purged gas coolant,the device is able to reach ultra-fast cooling rates of up to 40,000 K·s^(−1).Four thermal regions are identified by examining the cooling behaviors of two metallic glasses.This is because the actual rate of the specimen can differ from the programmed rate,especially at high set rate when the actual rate decreases before the glass transition is completed.We define the operational window for reliable cooling curve analysis,build models with empirical and theoretical analyses to determine the maximum feasible cooling rate,and demonstrate how optimizing sample mass and environment temperature broaden this window.The method avoids deceptive structural relaxation effects verified by fictivetemperature analysis and permits the capture of full glass transition during cooling.
基金The work described in this paper was fully supported by a grant from Hong Kong Metropolitan University(RIF/2021/05).
文摘Parkinson’s disease(PD)is a debilitating neurological disorder affecting over 10 million people worldwide.PD classification models using voice signals as input are common in the literature.It is believed that using deep learning algorithms further enhances performance;nevertheless,it is challenging due to the nature of small-scale and imbalanced PD datasets.This paper proposed a convolutional neural network-based deep support vector machine(CNN-DSVM)to automate the feature extraction process using CNN and extend the conventional SVM to a DSVM for better classification performance in small-scale PD datasets.A customized kernel function reduces the impact of biased classification towards the majority class(healthy candidates in our consideration).An improved generative adversarial network(IGAN)was designed to generate additional training data to enhance the model’s performance.For performance evaluation,the proposed algorithm achieves a sensitivity of 97.6%and a specificity of 97.3%.The performance comparison is evaluated from five perspectives,including comparisons with different data generation algorithms,feature extraction techniques,kernel functions,and existing works.Results reveal the effectiveness of the IGAN algorithm,which improves the sensitivity and specificity by 4.05%–4.72%and 4.96%–5.86%,respectively;and the effectiveness of the CNN-DSVM algorithm,which improves the sensitivity by 1.24%–57.4%and specificity by 1.04%–163%and reduces biased detection towards the majority class.The ablation experiments confirm the effectiveness of individual components.Two future research directions have also been suggested.
基金financially supported by the National Natural Science Foundation of China(No.52203209)the State Key Laboratory of Solid Waste Reuse for Building Materials,China(No.SWR-2022-009)the Fundamental Research Funds for the Central Universities,China(No.FRF-IDRY22-012)。
文摘Silver nanoparticles(Ag NPs)have attracted attention in the field of biomaterials due to their excellent antibacterial property.However,the reducing and stabilizing agents used for the chemical reduction of Ag NPs are usually toxic and may cause water pollution.In this work,Ag NPs(31.2 nm in diameter)were prepared using the extract of straw,an agricultural waste,as the reducing and stabilizing agent.Experimental analysis revealed that the straw extract contained lignin,the structure of which possesses phenolic hydroxyl and methoxy groups that facilitate the reduction of silver salts into Ag NPs.The surfaces of Ag NPs were negatively charged due to the encapsulation of a thin layer of lignin molecules that prevented their aggregation.After the prepared Ag NPs were added to the precursor solution of acrylamide,free radical polymerization was triggered without the need for extra heating or light irradiation,resulting in the rapid formation of an Ag NP-polyacrylamide composite hydrogel.The inhibition zone test proved that the composite hydrogel possessed excellent antibacterial ability due to the presence of Ag NPs.The prepared hydrogel may have potential applications in the fabrication of biomedical materials,such as antibacterial dressings.
文摘采用顶空固相微萃取(headspace solid-phase microextraction,HS-SPME)和液液萃取(liquid-liquid extraction,LLE)结合全二维气相色谱飞行时间质谱(comprehensive two-dimensional gas chromatography time of flight mass spectrometry,GC×GC-TOF-MS)以及香气活度值(odour active value,OAV),对红星二锅头白酒的挥发性成分进行全面解析。研究发现,HS-SPME、LLE分别定性出928、802种挥发性化合物,共计定性出1304种挥发性化合物,共同定性出426种挥发性化合物。基于HS-SPME数据,通过香气数据库筛选出具有香气特征的382种香气化合物,其中酯类相对百分含量占比最高,其次是醇类、酸类和醛类。计算得到了49种香气化合物OAV>1,其中酯类(辛酸乙酯、异戊酸乙酯等)和萜烯类(β-大马酮)对白酒风味的贡献最大,醛类(异戊醛、己醛等)和含硫类(二甲基三硫)其次,醇类(1-辛烯-3-醇)和含氮类(2,3,5-三甲基吡嗪)也有一定风味贡献。该研究丰富了红星二锅头白酒的风味研究,也为下一步生产研究及调控提供了理论和数据支撑。
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 use of fresh versus frozen spermatozoa in men with nonobstructive azoospermia (NOA) undergoingin vitro fertilization (IVF)has been a debated hot topic among reproductive specialists. Each approach presents distinct advantages and disadvantages,with fresh sperm typically showing superior sperm quality, while frozen sperm offers logistical flexibility and a reliable backup forrepeated cycles. This review summarizes the latest advancements in sperm retrieval and cryopreservation techniques, providingpractitioners with a comprehensive analysis of each option’s strengths and limitations. Comparative studies indicate that, althoughfresh sperm often has better quality metrics, cryopreservation methods such as vitrification have significantly improved postthawoutcomes, making frozen sperm a viable choice in assisted reproductive technologies (ART). The findings show comparablerates for fertilization, implantation, clinical pregnancy, and live birth between fresh and frozen microdissection testicular spermextraction (micro-TESE) sperm in many cases, although patient-specific factors such as timing, cost-effectiveness, and proceduralconvenience should guide the final decision. Ultimately, the choice of using fresh or frozen sperm should align with the individualneeds and conditions of patients. This tailored approach, supported by the latest advancements, can optimize ART outcomes andprovide personalized reproductive care.
基金supported by the Science and Technology Development Plan Project of Jilin Provincial Department of Science and Technology (No.20220203112S)the Jilin Provincial Department of Education Science and Technology Research Project (No.JJKH20210039KJ)。
文摘In this study,eight different varieties of maize seeds were used as the research objects.Conduct 81 types of combined preprocessing on the original spectra.Through comparison,Savitzky-Golay(SG)-multivariate scattering correction(MSC)-maximum-minimum normalization(MN)was identified as the optimal preprocessing technique.The competitive adaptive reweighted sampling(CARS),successive projections algorithm(SPA),and their combined methods were employed to extract feature wavelengths.Classification models based on back propagation(BP),support vector machine(SVM),random forest(RF),and partial least squares(PLS)were established using full-band data and feature wavelengths.Among all models,the(CARS-SPA)-BP model achieved the highest accuracy rate of 98.44%.This study offers novel insights and methodologies for the rapid and accurate identification of corn seeds as well as other crop seeds.
基金supported by CACMS Innovation Fund(No CI2021A04611,CI2021A05106)Scientific and technological innovation project of China Academy of Chinese Medical Sciences(CI2021B015)+1 种基金Scientific and technological innovation project of China Academy of Chinese Medical Sciences(CI2023E001TS01)Fundamental research funds for the central public welfare research institutes(L2022035).
文摘Objective Emerging evidence suggests that exposure to ultrafine particulate matter(UPM,aerodynamic diameter<0.1μm)is associated with adverse cardiovascular events.Previous studies have found that Shenlian(SL)extract possesses anti-inflammatory and antiapoptotic properties and has a promising protective effect at all stages of the atherosclerotic disease process.In this study,we aimed to investigated whether SL improves UPM-aggravated myocardial ischemic injury by inhibiting inflammation and cell apoptosis.Methods We established a mouse model of MI+UPM.Echocardiographic measurement,measurement of myocardialinfarct size,biochemical analysis,enzyme-linked immunosorbent assay(ELISA),histopathological analysis,Transferase dUTP Nick End Labeling(TUNEL),Western blotting(WB),Polymerase Chain Reaction(PCR)and so on were used to explore the anti-inflammatory and antiapoptotic effects of SL in vivo and in vitro.Results SL treatment can attenuate UPM-induced cardiac dysfunction by improving left ventricular ejection fraction,fractional shortening,and decreasing cardiac infarction area.SL significantly reduced the levels of myocardial enzymes and attenuated UPM-induced morphological alterations.Moreover,SL significantly reduced expression levels of the inflammatory cytokines IL-6,TNF-α,and MCP-1.UPM further increased the infiltration of macrophages in myocardial tissue,whereas SL intervention reversed this phenomenon.UPM also triggered myocardial apoptosis,which was markedly attenuated by SL treatment.The results of in vitro experiments revealed that SL prevented cell damage caused by exposure to UPM combined with hypoxia by reducing the expression of the inflammatory factor NF-κB and inhibiting apoptosis in H9c2 cells.Conclusion Overall,both in vivo and in vitro experiments demonstrated that SL attenuated UPMaggravated myocardial ischemic injury by inhibiting inflammation and cell apoptosis.The mechanisms were related to the downregulation of macrophages infiltrating heart tissues.
基金supported by the Science and Technology Development Fund,Macao SAR (Nos.0075/2022/A and028/2022/ITP)the Zhuhai Science and Technology Plan Project in the Social Development Field (No.2220004000117)the University of Macao (Nos.MYRG-GRG2023-00082-ICMS-UMDF/CPG2024-00011-ICMS)。
文摘The therapeutic efficacy of traditional Chinese medicine has been widely acknowledged due to its extensive history of clinical effectiveness.However,the precise active components underlying each prescription remain incompletely understood.Polysaccharides,as a major constituent of water decoctions—the most common preparation method for Chinese medicinals—may provide a crucial avenue for deepening our understanding of the efficacy principles of Chinese medicine and establishing a framework for its modern development.The structural complexity and diversity of Chinese herbal polysaccharides present significant challenges in their separation and analysis compared to small molecules.This paper aims to explore the potential of Chinese herbal polysaccharides efficiently by briefly summarizing recent advancements in polysaccharide chemical research,focusing on methods of acquisition,structure elucidation,and quality control.
基金financially supported by the National Natural Science Foundation of China(No.52161016)Joint Key Project of Agricultural Fundamental Research in Yunnan Provinceg(No.202101BD070001-017)+3 种基金Yunnan Provincial Academician Workstation(No.202305AF150009)Yunnan Province Natural Science Key Foundation(No.202201AS070152)Special Project of“Top Young Talents”of Yunnan Ten Thousand Talents Plan(No.51900109)Special Project of"Leading Talents of Industrial Technology"of Yunnan Ten Thousand Talents Plan(No.80201408).
文摘The inhibitory properties of rapeseed cake meal extract(RCME)on the corrosion of cold rolled steel(CRS)in trichloroacetic acid(TCA)were systematically investigated using gravimetric,electrochemical,surface characterizations and theoretical calculations.The results demonstrate that RCME exhibits excellent inhibitory performance with a maximum inhibition efficiency of 92.7%for 100 mg L−1 RCME at 20℃.The adsorption of RCME obeys Langmuir isotherm at 20 and 30℃,Temkin isotherm at 40℃,and Freundlich isotherm at 50℃.RCME acts as a cathodic inhibitor.The charge transfer resistance is increased with the addition of RCME,while the double-layer capacitance decreases.SEM,AFM,CLSM,XPS,XRD and TOF-SIMS analyses confirm that the active components in RCME adsorb onto the surface of CRS,forming a protective film that effectively inhibits the corrosion of CRS by TCA.Along with the increase in the concentration of RCME,the surface tension of the inhibited solution gradually decreases,while the electrical conductivity increases before stabilizing.HPLC-MS and FTIR analyses reveal rutin,linolenic acid,linoleic acid and adenine are the effective substances in RCME.Quantum chemical(QC)calculations and molecular dynamic(MD)simulations indicate that the active centers of the effective inhibitor molecules are predominantly located on benzene rings,O-or N-containing heterocyclic rings,and functional groups such as C=O and C=C.Additionally,their main chains adsorb onto the Fe(001)surface in an approximately flat manner,involving both chemical and physical adsorption processes.
基金supported by the National Natural Science Foundation of China(No.52188102).
文摘Anomaly Detection (AD) has been extensively adopted in industrial settings to facilitate quality control of products. It is critical to industrial production, especially to areas such as aircraft manufacturing, which require strict part qualification rates. Although being more efficient and practical, few-shot AD has not been well explored. The existing AD methods only extract features in a single frequency while defects exist in multiple frequency domains. Moreover, current methods have not fully leveraged the few-shot support samples to extract input-related normal patterns. To address these issues, we propose an industrial few-shot AD method, Feature Extender for Anomaly Detection (FEAD), which extracts normal patterns in multiple frequency domains from few-shot samples under the guidance of the input sample. Firstly, to achieve better coverage of normal patterns in the input sample, we introduce a Sample-Conditioned Transformation Module (SCTM), which transforms support features under the guidance of the input sample to obtain extra normal patterns. Secondly, to effectively distinguish and localize anomaly patterns in multiple frequency domains, we devise an Adaptive Descriptor Construction Module (ADCM) to build and select pattern descriptors in a series of frequencies adaptively. Finally, an auxiliary task for SCTM is designed to ensure the diversity of transformations and include more normal patterns into support features. Extensive experiments on two widely used industrial AD datasets (MVTec-AD and VisA) demonstrate the effectiveness of the proposed FEAD.
基金supported by the National Natural Science Foundation of China(Nos.32301259,32101228,32271527 and 32371536)the“Pioneer”and“Leading Goose”R&D Program of Zhejiang(Nos.2022C02023 and 2023C02015)+1 种基金the Research Foundation of Talented Scholars of Zhejiang A&F University(No.2021LFR058)the Dean-ship of Scientific Research at Northern Border University,Arar,KSA for funding this research work through the project number“NBU-FPEJ-2024-177-01”.
文摘As a typical bioflavonoid,diosmetin is desirable in the field of natural medicine,healthy food,and cosmetics by anti-cancer,antibacterial,antioxidant,estrogen-like and anti-inflammatory activities,and it comes from a wide range of sources in traditional Chinese medicine like spider fragrance,spearmint and chrysanthemum,as well as in Citrus fruit.However,traditional analytical methods such as silica gel column chromatography face multiple challenges in the selective extraction of diosmetin from biological materials and traditional Chinese medicinal materials.Therefore,it is urgent to develop a new type of absorbent with high efficiency,recyclability and good specificity to diosmetin.In this investigation,a magnetic surface molecularly imprinted polymer(labeled as Diosmetin/SMIPs)was synthesized employing magnetic nanoparticles as the carrier and 4-vinylpyridinyl(4-VP)as the functional monomer by surface imprinting technology.The functional monomer was screened by the binding energy(△E)between functional monomers and template molecules via computational simulation.The Diosmetin/SMIPs had a high level of specific recognition and adsorption capability towards diosmetin with a 20.25 mg g^(-1) adsorption capacity and an imprinting factor(IF)of 2.28.Additionally,it demonstrated excellent regeneration performance with 8 adsorption/desorption cycles.In addition,91.20%-94.16% of spiked diosmetin was recovered from the lemon peel samples.The strategy of constructing Diosmetin/SMIPs based on computational simulation can effectively enhance the specific adsorption performance of diosmetin.Meanwhile,Diosmetin/SMIPs synthesized by imprinting polymerization showed excellent anti-interference and reusability,and realized efficient targeted extraction of diosmetin from lemon peel samples.The results of this investigation provide a promising adsorbent for selective enrichment of diosmetin from Citrus fruit and complicated materials.
基金supported by the National Natural Science Foundation of Shandong(No.ZR2020ZD20)the National Natural Science Foundation of China(No.22193051)+1 种基金the National Young Top-Notch Talents(No.W03070030)the Youth Innovation Promotion Association of the Chinese Academy of Sciences(No.Y202011).
文摘Identification of the most appropriate chemically extractable pool for evaluating Cd and Pb availability remains elusive,hindering accurate assessment on environmental risks and effectiveness of remediation strategies.This study evaluated the feasibility of European Community Bureau of Reference(BCR)sequential extraction,Ca(NO_(3))_(2)extraction,and water extraction on assessing Cd and Pb availability in agricultural soil amended with slaked lime,magnesium hydroxide,corn stover biochar,and calcium dihydrogen phosphate.Moreover,the enriched isotope tracing technique(^(112)Cd and^(206)Pb)was employed to evaluate the aging process of newly introduced Cd and Pbwithin 56 days’incubation.Results demonstrated that extractable pools by BCR and Ca(NO_(3))_(2)extraction were little impacted by amendments and showed little correlation with soil pH.This is notable because soil pH is closely linked to metal availability,indicating these extraction methods may not adequately reflect metal availability.Conversely,water-soluble concentrations of Cd and Pb were markedly influenced by amendments and exhibited strong correlations with pH(Pearson’s r:-0.908 to-0.825,P<0.001),suggesting water extraction as a more sensitive approach.Furthermore,newly introduced metals underwent a more evident aging process as demonstrated by acid-soluble and water-soluble pools.Additionally,water-soluble concentrations of essential metals were impacted by soil amendments,raising caution on their potential effects on plant growth.These findings suggest water extraction as a promising and attractive method to evaluate Cd and Pb availability,which will help provide assessment guidance for environmental risks caused by heavy metals and develop efficient remediation strategies.
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.
