In this study,the structural characters,antioxidant activities and bile acid-binding ability of sea buckthorn polysaccharides(HRPs)obtained by the commonly used hot water(HRP-W),pressurized hot water(HRP-H),ultrasonic...In this study,the structural characters,antioxidant activities and bile acid-binding ability of sea buckthorn polysaccharides(HRPs)obtained by the commonly used hot water(HRP-W),pressurized hot water(HRP-H),ultrasonic(HRP-U),acid(HRP-C)and alkali(HRP-A)assisted extraction methods were investigated.The results demonstrated that extraction methods had significant effects on extraction yield,monosaccharide composition,molecular weight,particle size,triple-helical structure,and surface morphology of HRPs except for the major linkage bands.Thermogravimetric analysis showed that HRP-U with filamentous reticular microstructure exhibited better thermal stability.The HRP-A with the lowest molecular weight and highest arabinose content possessed the best antioxidant activities.Moreover,the rheological analysis indicated that HRPs with higher galacturonic acid content and molecular weight showed higher viscosity and stronger crosslinking network(HRP-C,HRP-W and HRP-U),which exhibited stronger bile acid binding capacity.The present findings provide scientific evidence in the preparation technology of sea buckthorn polysaccharides with good antioxidant and bile acid binding capacity which are related to the structure affected by the extraction methods.展开更多
Background Ginkgo biloba extract(GBE)is evidenced to be effective in the prevention and alleviation of metabolic disorders,including obesity,diabetes and fatty liver disease.However,the role of GBE in alleviating fatt...Background Ginkgo biloba extract(GBE)is evidenced to be effective in the prevention and alleviation of metabolic disorders,including obesity,diabetes and fatty liver disease.However,the role of GBE in alleviating fatty liver hemorrhagic syndrome(FLHS)in laying hens and the underlying mechanisms remain to be elucidated.Here,we investigated the effects of GBE on relieving FLHS with an emphasis on the modulatory role of GBE in chicken gut microbiota.Results The results showed that GBE treatment ameliorated biochemical blood indicators in high-fat diet(HFD)-induced FLHS laying hen model by decreasing the levels of TG,TC,ALT and ALP.The lipid accumulation and pathological score of liver were also relieved after GBE treatment.Moreover,GBE treatment enhanced the antioxidant activity of liver and serum by increasing GSH,SOD,T-AOC,GSH-PX and reducing MDA,and downregulated the expression of genes related to lipid synthesis(FAS,LXRα,GPAT1,PPARγand Ch REBP1)and inflammatory cytokines(TNF-α,IL-6,TLR4 and NF-κB)in the liver.Microbial profiling analysis revealed that GBE treatment reshaped the HFD-perturbed gut microbiota,particularly elevated the abundance of Megasphaera in the cecum.Meanwhile,targeted metabolomic analysis of SCFAs revealed that GBE treatment significantly promoted the production of total SCFAs,acetate and propionate,which were positively correlated with the GBE-enriched gut microbiota.Finally,we confirmed that the GBE-altered gut microbiota was sufficient to alleviate FLHS by fecal microbiota transplantation(FMT).Conclusions We provided evidence that GBE alleviated FLHS in HFD-induced laying hens through reshaping the composition of gut microbiota.Our findings shed light on mechanism underlying the anti-FLHS efficacy of GBE and lay foundations for future use of GBE as additive to prevent and control FLHS in laying hen industry.展开更多
A network intrusion detection system is critical for cyber security against llegitimate attacks.In terms of feature perspectives,network traffic may include a variety of elements such as attack reference,attack type,a...A network intrusion detection system is critical for cyber security against llegitimate attacks.In terms of feature perspectives,network traffic may include a variety of elements such as attack reference,attack type,a subcategory of attack,host information,malicious scripts,etc.In terms of network perspectives,network traffic may contain an imbalanced number of harmful attacks when compared to normal traffic.It is challenging to identify a specific attack due to complex features and data imbalance issues.To address these issues,this paper proposes an Intrusion Detection System using transformer-based transfer learning for Imbalanced Network Traffic(IDS-INT).IDS-INT uses transformer-based transfer learning to learn feature interactions in both network feature representation and imbalanced data.First,detailed information about each type of attack is gathered from network interaction descriptions,which include network nodes,attack type,reference,host information,etc.Second,the transformer-based transfer learning approach is developed to learn detailed feature representation using their semantic anchors.Third,the Synthetic Minority Oversampling Technique(SMOTE)is implemented to balance abnormal traffic and detect minority attacks.Fourth,the Convolution Neural Network(CNN)model is designed to extract deep features from the balanced network traffic.Finally,the hybrid approach of the CNN-Long Short-Term Memory(CNN-LSTM)model is developed to detect different types of attacks from the deep features.Detailed experiments are conducted to test the proposed approach using three standard datasets,i.e.,UNsWNB15,CIC-IDS2017,and NSL-KDD.An explainable AI approach is implemented to interpret the proposed method and develop a trustable model.展开更多
Active ingredients from highland barley have received considerable attention as natural products for developing treatments and dietary supplements against obesity.In practical application,the research of food combinat...Active ingredients from highland barley have received considerable attention as natural products for developing treatments and dietary supplements against obesity.In practical application,the research of food combinations is more significant than a specific food component.This study investigated the lipid-lowering effect of highland barley polyphenols via lipase assay in vitro and HepG2 cells induced by oleic acid(OA).Five indexes,triglyceride(TG),total cholesterol(T-CHO),low density lipoprotein-cholesterol(LDL-C),aspartate aminotransferase(AST),and alanine aminotransferase(ALT),were used to evaluate the lipidlowering effect of highland barley extract.We also preliminary studied the lipid-lowering mechanism by Realtime fluorescent quantitative polymerase chain reaction(q PCR).The results indicated that highland barley extract contains many components with lipid-lowering effects,such as hyperoside and scoparone.In vitro,the lipase assay showed an 18.4%lipase inhibition rate when the additive contents of highland barley extract were 100μg/m L.The intracellular lipid-lowering effect of highland barley extract was examined using 0.25 mmol/L OA-induced HepG2 cells.The results showed that intracellular TG,LDL-C,and T-CHO content decreased by 34.4%,51.2%,and 18.4%,respectively.ALT and AST decreased by 51.6%and 20.7%compared with the untreated hyperlipidemic HepG2 cells.q PCR results showed that highland barley polyphenols could up-regulation the expression of lipid metabolism-related genes such as PPARγand Fabp4.展开更多
240 nm AlGaN-based micro-LEDs with different sizes are designed and fabricated.Then,the external quantum efficiency(EQE)and light extraction efficiency(LEE)are systematically investigated by comparing size and edge ef...240 nm AlGaN-based micro-LEDs with different sizes are designed and fabricated.Then,the external quantum efficiency(EQE)and light extraction efficiency(LEE)are systematically investigated by comparing size and edge effects.Here,it is revealed that the peak optical output power increases by 81.83%with the size shrinking from 50.0 to 25.0μm.Thereinto,the LEE increases by 26.21%and the LEE enhancement mainly comes from the sidewall light extraction.Most notably,transversemagnetic(TM)mode light intensifies faster as the size shrinks due to the tilted mesa side-wall and Al reflector design.However,when it turns to 12.5μm sized micro-LEDs,the output power is lower than 25.0μm sized ones.The underlying mechanism is that even though protected by SiO2 passivation,the edge effect which leads to current leakage and Shockley-Read-Hall(SRH)recombination deteriorates rapidly with the size further shrinking.Moreover,the ratio of the p-contact area to mesa area is much lower,which deteriorates the p-type current spreading at the mesa edge.These findings show a role of thumb for the design of high efficiency micro-LEDs with wavelength below 250 nm,which will pave the way for wide applications of deep ultraviolet(DUV)micro-LEDs.展开更多
Condensed and hydrolysable tannins are non-toxic natural polyphenols that are a commercial commodity industrialized for tanning hides to obtain leather and for a growing number of other industrial applications mainly ...Condensed and hydrolysable tannins are non-toxic natural polyphenols that are a commercial commodity industrialized for tanning hides to obtain leather and for a growing number of other industrial applications mainly to substitute petroleum-based products.They are a definite class of sustainable materials of the forestry industry.They have been in operation for hundreds of years to manufacture leather and now for a growing number of applications in a variety of other industries,such as wood adhesives,metal coating,pharmaceutical/medical applications and several others.This review presents the main sources,either already or potentially commercial of this forestry by-materials,their industrial and laboratory extraction systems,their systems of analysis with their advantages and drawbacks,be these methods so simple to even appear primitive but nonetheless of proven effectiveness,or very modern and instrumental.It constitutes a basic but essential summary of what is necessary to know of these sustainable materials.In doing so,the review highlights some of the main challenges that remain to be addressed to deliver the quality and economics of tannin supply necessary to fulfill the industrial production requirements for some materials-based uses.展开更多
The current therapeutic drugs for Alzheimer's disease only improve symptoms,they do not delay disease progression.Therefo re,there is an urgent need for new effective drugs.The underlying pathogenic factors of Alz...The current therapeutic drugs for Alzheimer's disease only improve symptoms,they do not delay disease progression.Therefo re,there is an urgent need for new effective drugs.The underlying pathogenic factors of Alzheimer's disease are not clear,but neuroinflammation can link various hypotheses of Alzheimer's disease;hence,targeting neuroinflammation may be a new hope for Alzheimer's disease treatment.Inhibiting inflammation can restore neuronal function,promote neuro regeneration,reduce the pathological burden of Alzheimer's disease,and improve or even reverse symptoms of Alzheimer's disease.This review focuses on the relationship between inflammation and various pathological hypotheses of Alzheimer's disease;reports the mechanisms and characteristics of small-molecule drugs(e.g.,nonsteroidal anti-inflammatory drugs,neurosteroids,and plant extracts);macromolecule drugs(e.g.,peptides,proteins,and gene therapeutics);and nanocarriers(e.g.,lipid-based nanoparticles,polymeric nanoparticles,nanoemulsions,and inorganic nanoparticles)in the treatment of Alzheimer's disease.The review also makes recommendations for the prospective development of anti-inflammatory strategies based on nanocarriers for the treatment of Alzheimer's disease.展开更多
An efficient mass transfer process is a critical factor for regulating catalytic activity in a photocatalytic desulfurization system.Herein,a phosphotungstic acid(HPW)active center is successfully composited with a qu...An efficient mass transfer process is a critical factor for regulating catalytic activity in a photocatalytic desulfurization system.Herein,a phosphotungstic acid(HPW)active center is successfully composited with a quaternary ammonium phosphotungstate-based hexadecyltrimethylammonium chloride ionic liquid(CTAC-HPW)by the ion exchange method for the photocatalytic oxidative desulfurization of dibenzothiophene sulfide.The keggin structure of HPW and highly mass transfer performance of organic cations synergistically enhanced the photocatalytic activity towards the effective convertion of dibenzothiophene(DBT)with the excitation of visible light.The deep desulfurization(<10 mg·kg^(-1))is attained within 30 min,and well stability is demonstrated within 25 cycles.Moreover,the CTAC-HPW photocatalyst projects well selectivity to interference from coexisting compounds such as olefins and aromatic hydrocarbons and universality of dibenzothiophenes,for example,4-methyldibenzothiophene(4-MDBT)and 4,6-dimethyldibenzothiophene(4,6-DMDBT).Ultimately,a possible photocatalytic desulfurization mechanism is proposed according to the Gaschromatography-mass spectrometry(GC-MS),proving that the final product is the corresponding sulfone.The trapping experiment and electron spin resonance(ESR)analysis confirmed that h^(+)and,COOH played critical roles in the oxidation process.The work offers a practicable strategy for efficiently converting DBT to DBTO_(2) with added value.展开更多
Chemical solvents instead of pure water being as hydraulic fracturing fluid could effectively increase permeability and improve clean methane extraction efficiency.However,pore-fracture variation features of lean coal...Chemical solvents instead of pure water being as hydraulic fracturing fluid could effectively increase permeability and improve clean methane extraction efficiency.However,pore-fracture variation features of lean coal synergistically affected by solvents have not been fully understood.Ultrasonic testing,nuclear magnetic resonance analysis,liquid phase mass spectrometry was adopted to comprehensively analyze pore-fracture change characteristics of lean coal treated by combined solvent(NMP and CS_(2)).Meanwhile,quantitative characterization of above changing properties was conducted using geometric fractal theory.Relationship model between permeability,fractal dimension and porosity were established.Results indicate that the end face fractures of coal are well developed after CS2and combined solvent treatments,of which,end face box-counting fractal dimensions range from 1.1227 to 1.4767.Maximum decreases in ultrasonic longitudinal wave velocity of coal affected by NMP,CS_(2)and combined solvent are 2.700%,20.521%,22.454%,respectively.Solvent treatments could lead to increasing amount of both mesopores and macropores.Decrease ratio of fractal dimension Dsis 0.259%–2.159%,while permeability increases ratio of NMR ranges from 0.1904 to 6.4486.Meanwhile,combined solvent could dissolve coal polar and non-polar small molecules and expand flow space.Results could provide reference for solvent selection and parameter optimization of permeability-enhancement technology.展开更多
An artificial neural network(ANN)method is introduced to predict drop size in two kinds of pulsed columns with small-scale data sets.After training,the deviation between calculate and experimental results are 3.8%and ...An artificial neural network(ANN)method is introduced to predict drop size in two kinds of pulsed columns with small-scale data sets.After training,the deviation between calculate and experimental results are 3.8%and 9.3%,respectively.Through ANN model,the influence of interfacial tension and pulsation intensity on the droplet diameter has been developed.Droplet size gradually increases with the increase of interfacial tension,and decreases with the increase of pulse intensity.It can be seen that the accuracy of ANN model in predicting droplet size outside the training set range is reach the same level as the accuracy of correlation obtained based on experiments within this range.For two kinds of columns,the drop size prediction deviations of ANN model are 9.6%and 18.5%and the deviations in correlations are 11%and 15%.展开更多
Modern medicine is reliant on various medical imaging technologies for non-invasively observing patients’anatomy.However,the interpretation of medical images can be highly subjective and dependent on the expertise of...Modern medicine is reliant on various medical imaging technologies for non-invasively observing patients’anatomy.However,the interpretation of medical images can be highly subjective and dependent on the expertise of clinicians.Moreover,some potentially useful quantitative information in medical images,especially that which is not visible to the naked eye,is often ignored during clinical practice.In contrast,radiomics performs high-throughput feature extraction from medical images,which enables quantitative analysis of medical images and prediction of various clinical endpoints.Studies have reported that radiomics exhibits promising performance in diagnosis and predicting treatment responses and prognosis,demonstrating its potential to be a non-invasive auxiliary tool for personalized medicine.However,radiomics remains in a developmental phase as numerous technical challenges have yet to be solved,especially in feature engineering and statistical modeling.In this review,we introduce the current utility of radiomics by summarizing research on its application in the diagnosis,prognosis,and prediction of treatment responses in patients with cancer.We focus on machine learning approaches,for feature extraction and selection during feature engineering and for imbalanced datasets and multi-modality fusion during statistical modeling.Furthermore,we introduce the stability,reproducibility,and interpretability of features,and the generalizability and interpretability of models.Finally,we offer possible solutions to current challenges in radiomics research.展开更多
To solve the problem of poor detection and limited application range of current intrusion detection methods,this paper attempts to use deep learning neural network technology to study a new type of intrusion detection...To solve the problem of poor detection and limited application range of current intrusion detection methods,this paper attempts to use deep learning neural network technology to study a new type of intrusion detection method.Hence,we proposed an intrusion detection algorithm based on convolutional neural network(CNN)and AdaBoost algorithm.This algorithm uses CNN to extract the characteristics of network traffic data,which is particularly suitable for the analysis of continuous and classified attack data.The AdaBoost algorithm is used to classify network attack data that improved the detection effect of unbalanced data classification.We adopt the UNSW-NB15 dataset to test of this algorithm in the PyCharm environment.The results show that the detection rate of algorithm is99.27%and the false positive rate is lower than 0.98%.Comparative analysis shows that this algorithm has advantages over existing methods in terms of detection rate and false positive rate for small proportion of attack data.展开更多
A large number of network security breaches in IoT networks have demonstrated the unreliability of current Network Intrusion Detection Systems(NIDSs).Consequently,network interruptions and loss of sensitive data have ...A large number of network security breaches in IoT networks have demonstrated the unreliability of current Network Intrusion Detection Systems(NIDSs).Consequently,network interruptions and loss of sensitive data have occurred,which led to an active research area for improving NIDS technologies.In an analysis of related works,it was observed that most researchers aim to obtain better classification results by using a set of untried combinations of Feature Reduction(FR)and Machine Learning(ML)techniques on NIDS datasets.However,these datasets are different in feature sets,attack types,and network design.Therefore,this paper aims to discover whether these techniques can be generalised across various datasets.Six ML models are utilised:a Deep Feed Forward(DFF),Convolutional Neural Network(CNN),Recurrent Neural Network(RNN),Decision Tree(DT),Logistic Regression(LR),and Naive Bayes(NB).The accuracy of three Feature Extraction(FE)algorithms is detected;Principal Component Analysis(PCA),Auto-encoder(AE),and Linear Discriminant Analysis(LDA),are evaluated using three benchmark datasets:UNSW-NB15,ToN-IoT and CSE-CIC-IDS2018.Although PCA and AE algorithms have been widely used,the determination of their optimal number of extracted dimensions has been overlooked.The results indicate that no clear FE method or ML model can achieve the best scores for all datasets.The optimal number of extracted dimensions has been identified for each dataset,and LDA degrades the performance of the ML models on two datasets.The variance is used to analyse the extracted dimensions of LDA and PCA.Finally,this paper concludes that the choice of datasets significantly alters the performance of the applied techniques.We believe that a universal(benchmark)feature set is needed to facilitate further advancement and progress of research in this field.展开更多
AIM:To review recent innovations,challenges,and applications of small incision lenticule extraction(SMILE)extracted lenticule for treating ocular disorders.METHODS:A literature review was performed in the PubMed datab...AIM:To review recent innovations,challenges,and applications of small incision lenticule extraction(SMILE)extracted lenticule for treating ocular disorders.METHODS:A literature review was performed in the PubMed database,which was last updated on 30 December 2021.There was no limit regarding language.The authors evaluated the reference lists of the collected papers to find any relevant research.RESULTS:Due to the simplicity and accuracy of modern femtosecond lasers and the extensive development of SMILE surgery,many healthy human corneal stromal lenticules were extracted during surgery,motivating some professionals to investigate the SMILE lenticule reusability in different ocular disorders.In addition,new approaches had been developed to preserve,modify,and bioengineer the corneal stroma,leading to the optimal use of discarded byproducts such as lenticules from SMILE surgery.The lenticules can be effectively re-implanted into the autologous or allogenic corneas of human subjects to treat refractive errors,corneal ectasia,and corneal perforation and serve as a patch graft for glaucoma drainage devices with better cosmetic outcomes.CONCLUSION:SMILE-extracted lenticules could be a viable alternative to human donor corneal tissue.展开更多
Lithium recovery from spent lithium-ion batteries(LIBs)have attracted extensive attention due to the skyrocketing price of lithium.The medium-temperature carbon reduction roasting was proposed to preferential selectiv...Lithium recovery from spent lithium-ion batteries(LIBs)have attracted extensive attention due to the skyrocketing price of lithium.The medium-temperature carbon reduction roasting was proposed to preferential selective extraction of lithium from spent Li-CoO_(2)(LCO)cathodes to overcome the incomplete recovery and loss of lithium during the recycling process.The LCO layered structure was destroyed and lithium was completely converted into water-soluble Li2CO_(3)under a suitable temperature to control the reduced state of the cobalt oxide.The Co metal agglomerates generated during medium-temperature carbon reduction roasting were broken by wet grinding and ultrasonic crushing to release the entrained lithium.The results showed that 99.10%of the whole lithium could be recovered as Li2CO_(3)with a purity of 99.55%.This work provided a new perspective on the preferentially selective extraction of lithium from spent lithium batteries.展开更多
Cultural relics line graphic serves as a crucial form of traditional artifact information documentation,which is a simple and intuitive product with low cost of displaying compared with 3D models.Dimensionality reduct...Cultural relics line graphic serves as a crucial form of traditional artifact information documentation,which is a simple and intuitive product with low cost of displaying compared with 3D models.Dimensionality reduction is undoubtedly necessary for line drawings.However,most existing methods for artifact drawing rely on the principles of orthographic projection that always cannot avoid angle occlusion and data overlapping while the surface of cultural relics is complex.Therefore,conformal mapping was introduced as a dimensionality reduction way to compensate for the limitation of orthographic projection.Based on the given criteria for assessing surface complexity,this paper proposed a three-dimensional feature guideline extraction method for complex cultural relic surfaces.A 2D and 3D combined factor that measured the importance of points on describing surface features,vertex weight,was designed.Then the selection threshold for feature guideline extraction was determined based on the differences between vertex weight and shape index distributions.The feasibility and stability were verified through experiments conducted on real cultural relic surface data.Results demonstrated the ability of the method to address the challenges associated with the automatic generation of line drawings for complex surfaces.The extraction method and the obtained results will be useful for line graphic drawing,displaying and propaganda of cultural relics.展开更多
Timely acquisition of rescue target information is critical for emergency response after a flood disaster.Unmanned Aerial Vehicles(UAVs)equipped with remote sensing capabilities offer distinct advantages,including hig...Timely acquisition of rescue target information is critical for emergency response after a flood disaster.Unmanned Aerial Vehicles(UAVs)equipped with remote sensing capabilities offer distinct advantages,including high-resolution imagery and exceptional mobility,making them well suited for monitoring flood extent and identifying rescue targets during floods.However,there are some challenges in interpreting rescue information in real time from flood images captured by UAVs,such as the complexity of the scenarios of UAV images,the lack of flood rescue target detection datasets and the limited real-time processing capabilities of the airborne on-board platform.Thus,we propose a real-time rescue target detection method for UAVs that is capable of efficiently delineating flood extent and identifying rescue targets(i.e.,pedestrians and vehicles trapped by floods).The proposed method achieves real-time rescue information extraction for UAV platforms by lightweight processing and fusion of flood extent extraction model and target detection model.The flood inundation range is extracted by the proposed method in real time and detects targets such as people and vehicles to be rescued based on this layer.Our experimental results demonstrate that the Intersection over Union(IoU)for flood water extraction reaches an impressive 80%,and the IoU for real-time flood water extraction stands at a commendable 76.4%.The information on flood stricken targets extracted by this method in real time can be used for flood emergency rescue.展开更多
Electrochemical lithium extraction from salt lakes is an effective strategy for obtaining lithium at a low cost.Nevertheless,the elevated Mg:Li ratio and the presence of numerous coexisting ions in salt lake brines gi...Electrochemical lithium extraction from salt lakes is an effective strategy for obtaining lithium at a low cost.Nevertheless,the elevated Mg:Li ratio and the presence of numerous coexisting ions in salt lake brines give rise to challenges,such as prolonged lithium extraction periods,diminished lithium extraction efficiency,and considerable environmental pollution.In this work,Li FePO4(LFP)served as the electrode material for electrochemical lithium extraction.The conductive network in the LFP electrode was optimized by adjusting the type of conductive agent.This approach resulted in high lithium extraction efficiency and extended cycle life.When the single conductive agent of acetylene black(AB)or multiwalled carbon nanotubes(MWCNTs)was replaced with the mixed conductive agent of AB/MWCNTs,the average diffusion coefficient of Li+in the electrode increased from 2.35×10^(-9)or 1.77×10^(-9)to 4.21×10^(-9)cm^(2)·s^(-1).At the current density of 20 mA·g^(-1),the average lithium extraction capacity per gram of LFP electrode increased from 30.36 mg with the single conductive agent(AB)to 35.62 mg with the mixed conductive agent(AB/MWCNTs).When the mixed conductive agent was used,the capacity retention of the electrode after 30 cycles reached 82.9%,which was considerably higher than the capacity retention of 65.8%obtained when the single AB was utilized.Meanwhile,the electrode with mixed conductive agent of AB/MWCNTs provided good cycling performance.When the conductive agent content decreased or the loading capacity increased,the electrode containing the mixed conductive agent continued to show excellent electrochemical performance.Furthermore,a self-designed,highly efficient,continuous lithium extraction device was constructed.The electrode utilizing the AB/MWCNT mixed conductive agent maintained excellent adsorption capacity and cycling performance in this device.This work provides a new perspective for the electrochemical extraction of lithium using LFP electrodes.展开更多
Lithium recovery from end-of-life Li-ion batteries(LIBs)through pyro-and hydrometallurgical recycling processes involves several refining stages,with high consumption of reagents and energy.A competitive technological...Lithium recovery from end-of-life Li-ion batteries(LIBs)through pyro-and hydrometallurgical recycling processes involves several refining stages,with high consumption of reagents and energy.A competitive technological alternative is the electrochemical oxidation of the cathode materials,whereby lithium can be deintercalated and transferred to an electrolyte solution without the aid of chemical extracting compounds.This article investigates the potential to selectively recover Li from LIB cathode materials by direct electrochemical extraction in aqueous solutions.The process allowed to recovering up to 98%of Li from high-purity commercial cathode materials(LiMn_(2)O_(4),LiCoO_(2),and Li Ni_(1/3)Mn_(1/3)Co_(1/3)O_(2))with a faradaic efficiency of 98%and negligible co-extraction of Co,Ni,and Mn.The process was then applied to recover Li from the real waste LIBs black mass obtained by the physical treatment of electric vehicle battery packs.This black mass contained graphite,conductive carbon,and metal impurities from current collectors and steel cases,which significantly influenced the evolution and performances of Li electrochemical extraction.Particularly,due to concomitant oxidation of impurities,lithium extraction yields and faradaic efficiencies were lower than those obtained with high-purity cathode materials.Copper oxidation was found to occur within the voltage range investigated,but it could not quantitatively explain the reduced Li extraction performances.In fact,a detailed investigation revealed that above 1.3 V vs.Ag/Ag Cl,conductive carbon can be oxidized,contributing to the decreased Li extraction.Based on the reported experimental results,guidelines were provided that quantitatively enable the extraction of Li from the black mass,while preventing the simultaneous oxidation of impurities and,consequently,reducing the energy consumption of the proposed Li recovery method.展开更多
Purpose:The purpose of this study is to serve as a comprehensive review of the existing annotated corpora.This review study aims to provide information on the existing annotated corpora for event extraction,which are ...Purpose:The purpose of this study is to serve as a comprehensive review of the existing annotated corpora.This review study aims to provide information on the existing annotated corpora for event extraction,which are limited but essential for training and improving the existing event extraction algorithms.In addition to the primary goal of this study,it provides guidelines for preparing an annotated corpus and suggests suitable tools for the annotation task.Design/methodology/approach:This study employs an analytical approach to examine available corpus that is suitable for event extraction tasks.It offers an in-depth analysis of existing event extraction corpora and provides systematic guidelines for researchers to develop accurate,high-quality corpora.This ensures the reliability of the created corpus and its suitability for training machine learning algorithms.Findings:Our exploration reveals a scarcity of annotated corpora for event extraction tasks.In particular,the English corpora are mainly focused on the biomedical and general domains.Despite the issue of annotated corpora scarcity,there are several high-quality corpora available and widely used as benchmark datasets.However,access to some of these corpora might be limited owing to closed-access policies or discontinued maintenance after being initially released,rendering them inaccessible owing to broken links.Therefore,this study documents the available corpora for event extraction tasks.Research limitations:Our study focuses only on well-known corpora available in English and Chinese.Nevertheless,this study places a strong emphasis on the English corpora due to its status as a global lingua franca,making it widely understood compared to other languages.Practical implications:We genuinely believe that this study provides valuable knowledge that can serve as a guiding framework for preparing and accurately annotating events from text corpora.It provides comprehensive guidelines for researchers to improve the quality of corpus annotations,especially for event extraction tasks across various domains.Originality/value:This study comprehensively compiled information on the existing annotated corpora for event extraction tasks and provided preparation guidelines.展开更多
基金The Guangdong Basic and Applied Basic Research Foundation(2022A1515010730)National Natural Science Foundation of China(32001647)+2 种基金National Natural Science Foundation of China(31972022)Financial and moral assistance supported by the Guangdong Basic and Applied Basic Research Foundation(2019A1515011996)111 Project(B17018)。
文摘In this study,the structural characters,antioxidant activities and bile acid-binding ability of sea buckthorn polysaccharides(HRPs)obtained by the commonly used hot water(HRP-W),pressurized hot water(HRP-H),ultrasonic(HRP-U),acid(HRP-C)and alkali(HRP-A)assisted extraction methods were investigated.The results demonstrated that extraction methods had significant effects on extraction yield,monosaccharide composition,molecular weight,particle size,triple-helical structure,and surface morphology of HRPs except for the major linkage bands.Thermogravimetric analysis showed that HRP-U with filamentous reticular microstructure exhibited better thermal stability.The HRP-A with the lowest molecular weight and highest arabinose content possessed the best antioxidant activities.Moreover,the rheological analysis indicated that HRPs with higher galacturonic acid content and molecular weight showed higher viscosity and stronger crosslinking network(HRP-C,HRP-W and HRP-U),which exhibited stronger bile acid binding capacity.The present findings provide scientific evidence in the preparation technology of sea buckthorn polysaccharides with good antioxidant and bile acid binding capacity which are related to the structure affected by the extraction methods.
基金funded by the National Key Research and Development Program of China(2022YFA1304201)the Beijing Natural Science Foundation(6222032)+2 种基金the Starting Grants Program for Young Talents at China Agricultural Universitythe 2115 Talent Development Program of China Agricultural UniversityChinese Universities Scientific Fund。
文摘Background Ginkgo biloba extract(GBE)is evidenced to be effective in the prevention and alleviation of metabolic disorders,including obesity,diabetes and fatty liver disease.However,the role of GBE in alleviating fatty liver hemorrhagic syndrome(FLHS)in laying hens and the underlying mechanisms remain to be elucidated.Here,we investigated the effects of GBE on relieving FLHS with an emphasis on the modulatory role of GBE in chicken gut microbiota.Results The results showed that GBE treatment ameliorated biochemical blood indicators in high-fat diet(HFD)-induced FLHS laying hen model by decreasing the levels of TG,TC,ALT and ALP.The lipid accumulation and pathological score of liver were also relieved after GBE treatment.Moreover,GBE treatment enhanced the antioxidant activity of liver and serum by increasing GSH,SOD,T-AOC,GSH-PX and reducing MDA,and downregulated the expression of genes related to lipid synthesis(FAS,LXRα,GPAT1,PPARγand Ch REBP1)and inflammatory cytokines(TNF-α,IL-6,TLR4 and NF-κB)in the liver.Microbial profiling analysis revealed that GBE treatment reshaped the HFD-perturbed gut microbiota,particularly elevated the abundance of Megasphaera in the cecum.Meanwhile,targeted metabolomic analysis of SCFAs revealed that GBE treatment significantly promoted the production of total SCFAs,acetate and propionate,which were positively correlated with the GBE-enriched gut microbiota.Finally,we confirmed that the GBE-altered gut microbiota was sufficient to alleviate FLHS by fecal microbiota transplantation(FMT).Conclusions We provided evidence that GBE alleviated FLHS in HFD-induced laying hens through reshaping the composition of gut microbiota.Our findings shed light on mechanism underlying the anti-FLHS efficacy of GBE and lay foundations for future use of GBE as additive to prevent and control FLHS in laying hen industry.
文摘A network intrusion detection system is critical for cyber security against llegitimate attacks.In terms of feature perspectives,network traffic may include a variety of elements such as attack reference,attack type,a subcategory of attack,host information,malicious scripts,etc.In terms of network perspectives,network traffic may contain an imbalanced number of harmful attacks when compared to normal traffic.It is challenging to identify a specific attack due to complex features and data imbalance issues.To address these issues,this paper proposes an Intrusion Detection System using transformer-based transfer learning for Imbalanced Network Traffic(IDS-INT).IDS-INT uses transformer-based transfer learning to learn feature interactions in both network feature representation and imbalanced data.First,detailed information about each type of attack is gathered from network interaction descriptions,which include network nodes,attack type,reference,host information,etc.Second,the transformer-based transfer learning approach is developed to learn detailed feature representation using their semantic anchors.Third,the Synthetic Minority Oversampling Technique(SMOTE)is implemented to balance abnormal traffic and detect minority attacks.Fourth,the Convolution Neural Network(CNN)model is designed to extract deep features from the balanced network traffic.Finally,the hybrid approach of the CNN-Long Short-Term Memory(CNN-LSTM)model is developed to detect different types of attacks from the deep features.Detailed experiments are conducted to test the proposed approach using three standard datasets,i.e.,UNsWNB15,CIC-IDS2017,and NSL-KDD.An explainable AI approach is implemented to interpret the proposed method and develop a trustable model.
基金financially supported by the National Key Research and Development Program of China(2021YFD2100904)the National Natural Science Foundation of China(31871729,32172147)+2 种基金the Modern Agriculture key Project of Jiangsu Province of China(BE2022317)the Modern Agricultural Industrial Technology System Construction Project of Jiangsu Province of China(JATS[2021]522)a project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)。
文摘Active ingredients from highland barley have received considerable attention as natural products for developing treatments and dietary supplements against obesity.In practical application,the research of food combinations is more significant than a specific food component.This study investigated the lipid-lowering effect of highland barley polyphenols via lipase assay in vitro and HepG2 cells induced by oleic acid(OA).Five indexes,triglyceride(TG),total cholesterol(T-CHO),low density lipoprotein-cholesterol(LDL-C),aspartate aminotransferase(AST),and alanine aminotransferase(ALT),were used to evaluate the lipidlowering effect of highland barley extract.We also preliminary studied the lipid-lowering mechanism by Realtime fluorescent quantitative polymerase chain reaction(q PCR).The results indicated that highland barley extract contains many components with lipid-lowering effects,such as hyperoside and scoparone.In vitro,the lipase assay showed an 18.4%lipase inhibition rate when the additive contents of highland barley extract were 100μg/m L.The intracellular lipid-lowering effect of highland barley extract was examined using 0.25 mmol/L OA-induced HepG2 cells.The results showed that intracellular TG,LDL-C,and T-CHO content decreased by 34.4%,51.2%,and 18.4%,respectively.ALT and AST decreased by 51.6%and 20.7%compared with the untreated hyperlipidemic HepG2 cells.q PCR results showed that highland barley polyphenols could up-regulation the expression of lipid metabolism-related genes such as PPARγand Fabp4.
基金This work was supported by National Key R&D Program of China(2022YFB3605103)the National Natural Science Foundation of China(62204241,U22A2084,62121005,and 61827813)+3 种基金the Natural Science Foundation of Jilin Province(20230101345JC,20230101360JC,and 20230101107JC)the Youth Innovation Promotion Association of CAS(2023223)the Young Elite Scientist Sponsorship Program By CAST(YESS20200182)the CAS Talents Program(E30122E4M0).
文摘240 nm AlGaN-based micro-LEDs with different sizes are designed and fabricated.Then,the external quantum efficiency(EQE)and light extraction efficiency(LEE)are systematically investigated by comparing size and edge effects.Here,it is revealed that the peak optical output power increases by 81.83%with the size shrinking from 50.0 to 25.0μm.Thereinto,the LEE increases by 26.21%and the LEE enhancement mainly comes from the sidewall light extraction.Most notably,transversemagnetic(TM)mode light intensifies faster as the size shrinks due to the tilted mesa side-wall and Al reflector design.However,when it turns to 12.5μm sized micro-LEDs,the output power is lower than 25.0μm sized ones.The underlying mechanism is that even though protected by SiO2 passivation,the edge effect which leads to current leakage and Shockley-Read-Hall(SRH)recombination deteriorates rapidly with the size further shrinking.Moreover,the ratio of the p-contact area to mesa area is much lower,which deteriorates the p-type current spreading at the mesa edge.These findings show a role of thumb for the design of high efficiency micro-LEDs with wavelength below 250 nm,which will pave the way for wide applications of deep ultraviolet(DUV)micro-LEDs.
文摘Condensed and hydrolysable tannins are non-toxic natural polyphenols that are a commercial commodity industrialized for tanning hides to obtain leather and for a growing number of other industrial applications mainly to substitute petroleum-based products.They are a definite class of sustainable materials of the forestry industry.They have been in operation for hundreds of years to manufacture leather and now for a growing number of applications in a variety of other industries,such as wood adhesives,metal coating,pharmaceutical/medical applications and several others.This review presents the main sources,either already or potentially commercial of this forestry by-materials,their industrial and laboratory extraction systems,their systems of analysis with their advantages and drawbacks,be these methods so simple to even appear primitive but nonetheless of proven effectiveness,or very modern and instrumental.It constitutes a basic but essential summary of what is necessary to know of these sustainable materials.In doing so,the review highlights some of the main challenges that remain to be addressed to deliver the quality and economics of tannin supply necessary to fulfill the industrial production requirements for some materials-based uses.
基金supported by the National Natural Science Foundation of China,Nos.82072051 and 81771964(both to JG)the Natural Science Foundation of Shanghai Municipal Science and Technology Commission,No.22ZR147750(to YY)+2 种基金Science and Technology Support Projects in Biomedicine Field of Shanghai Science and Technology Commission,No.19441907500(to YY)Innovative Clinical Research Project of Changzheng Hospital,No.2020 YLCYJ-Y02(to YY)Characteristic Medical Service Project for the Army of Changzheng Hospital,No.2020 CZWJFW12(to YY)。
文摘The current therapeutic drugs for Alzheimer's disease only improve symptoms,they do not delay disease progression.Therefo re,there is an urgent need for new effective drugs.The underlying pathogenic factors of Alzheimer's disease are not clear,but neuroinflammation can link various hypotheses of Alzheimer's disease;hence,targeting neuroinflammation may be a new hope for Alzheimer's disease treatment.Inhibiting inflammation can restore neuronal function,promote neuro regeneration,reduce the pathological burden of Alzheimer's disease,and improve or even reverse symptoms of Alzheimer's disease.This review focuses on the relationship between inflammation and various pathological hypotheses of Alzheimer's disease;reports the mechanisms and characteristics of small-molecule drugs(e.g.,nonsteroidal anti-inflammatory drugs,neurosteroids,and plant extracts);macromolecule drugs(e.g.,peptides,proteins,and gene therapeutics);and nanocarriers(e.g.,lipid-based nanoparticles,polymeric nanoparticles,nanoemulsions,and inorganic nanoparticles)in the treatment of Alzheimer's disease.The review also makes recommendations for the prospective development of anti-inflammatory strategies based on nanocarriers for the treatment of Alzheimer's disease.
基金the financial supports from National Natural Science Foundation of China(22172066,22378176)supported by State Key Laboratory of Heavy Oil ProcessingSupported by Jiangsu Collaborative Innovation Center of Technology and Material of Water Treatment,Suzhou University of Science and Technology。
文摘An efficient mass transfer process is a critical factor for regulating catalytic activity in a photocatalytic desulfurization system.Herein,a phosphotungstic acid(HPW)active center is successfully composited with a quaternary ammonium phosphotungstate-based hexadecyltrimethylammonium chloride ionic liquid(CTAC-HPW)by the ion exchange method for the photocatalytic oxidative desulfurization of dibenzothiophene sulfide.The keggin structure of HPW and highly mass transfer performance of organic cations synergistically enhanced the photocatalytic activity towards the effective convertion of dibenzothiophene(DBT)with the excitation of visible light.The deep desulfurization(<10 mg·kg^(-1))is attained within 30 min,and well stability is demonstrated within 25 cycles.Moreover,the CTAC-HPW photocatalyst projects well selectivity to interference from coexisting compounds such as olefins and aromatic hydrocarbons and universality of dibenzothiophenes,for example,4-methyldibenzothiophene(4-MDBT)and 4,6-dimethyldibenzothiophene(4,6-DMDBT).Ultimately,a possible photocatalytic desulfurization mechanism is proposed according to the Gaschromatography-mass spectrometry(GC-MS),proving that the final product is the corresponding sulfone.The trapping experiment and electron spin resonance(ESR)analysis confirmed that h^(+)and,COOH played critical roles in the oxidation process.The work offers a practicable strategy for efficiently converting DBT to DBTO_(2) with added value.
基金financially supported by National Natural Science Foundation of China(No.52274171)Joint National-Local Engineering Research Centre for Safe and Precise Coal Mining Fund(No.EC2023015)+1 种基金Excellent Youth Project of Universities in Anhui Province(No.2023AH030042)Unveiled List of Bidding Projects of Shanxi Province(No.20201101001)。
文摘Chemical solvents instead of pure water being as hydraulic fracturing fluid could effectively increase permeability and improve clean methane extraction efficiency.However,pore-fracture variation features of lean coal synergistically affected by solvents have not been fully understood.Ultrasonic testing,nuclear magnetic resonance analysis,liquid phase mass spectrometry was adopted to comprehensively analyze pore-fracture change characteristics of lean coal treated by combined solvent(NMP and CS_(2)).Meanwhile,quantitative characterization of above changing properties was conducted using geometric fractal theory.Relationship model between permeability,fractal dimension and porosity were established.Results indicate that the end face fractures of coal are well developed after CS2and combined solvent treatments,of which,end face box-counting fractal dimensions range from 1.1227 to 1.4767.Maximum decreases in ultrasonic longitudinal wave velocity of coal affected by NMP,CS_(2)and combined solvent are 2.700%,20.521%,22.454%,respectively.Solvent treatments could lead to increasing amount of both mesopores and macropores.Decrease ratio of fractal dimension Dsis 0.259%–2.159%,while permeability increases ratio of NMR ranges from 0.1904 to 6.4486.Meanwhile,combined solvent could dissolve coal polar and non-polar small molecules and expand flow space.Results could provide reference for solvent selection and parameter optimization of permeability-enhancement technology.
基金the support of the National Natural Science Foundation of China(22278234,21776151)。
文摘An artificial neural network(ANN)method is introduced to predict drop size in two kinds of pulsed columns with small-scale data sets.After training,the deviation between calculate and experimental results are 3.8%and 9.3%,respectively.Through ANN model,the influence of interfacial tension and pulsation intensity on the droplet diameter has been developed.Droplet size gradually increases with the increase of interfacial tension,and decreases with the increase of pulse intensity.It can be seen that the accuracy of ANN model in predicting droplet size outside the training set range is reach the same level as the accuracy of correlation obtained based on experiments within this range.For two kinds of columns,the drop size prediction deviations of ANN model are 9.6%and 18.5%and the deviations in correlations are 11%and 15%.
基金supported in part by the National Natural Science Foundation of China(82072019)the Shenzhen Basic Research Program(JCYJ20210324130209023)+5 种基金the Shenzhen-Hong Kong-Macao S&T Program(Category C)(SGDX20201103095002019)the Mainland-Hong Kong Joint Funding Scheme(MHKJFS)(MHP/005/20),the Project of Strategic Importance Fund(P0035421)the Projects of RISA(P0043001)from the Hong Kong Polytechnic University,the Natural Science Foundation of Jiangsu Province(BK20201441)the Provincial and Ministry Co-constructed Project of Henan Province Medical Science and Technology Research(SBGJ202103038,SBGJ202102056)the Henan Province Key R&D and Promotion Project(Science and Technology Research)(222102310015)the Natural Science Foundation of Henan Province(222300420575),and the Henan Province Science and Technology Research(222102310322).
文摘Modern medicine is reliant on various medical imaging technologies for non-invasively observing patients’anatomy.However,the interpretation of medical images can be highly subjective and dependent on the expertise of clinicians.Moreover,some potentially useful quantitative information in medical images,especially that which is not visible to the naked eye,is often ignored during clinical practice.In contrast,radiomics performs high-throughput feature extraction from medical images,which enables quantitative analysis of medical images and prediction of various clinical endpoints.Studies have reported that radiomics exhibits promising performance in diagnosis and predicting treatment responses and prognosis,demonstrating its potential to be a non-invasive auxiliary tool for personalized medicine.However,radiomics remains in a developmental phase as numerous technical challenges have yet to be solved,especially in feature engineering and statistical modeling.In this review,we introduce the current utility of radiomics by summarizing research on its application in the diagnosis,prognosis,and prediction of treatment responses in patients with cancer.We focus on machine learning approaches,for feature extraction and selection during feature engineering and for imbalanced datasets and multi-modality fusion during statistical modeling.Furthermore,we introduce the stability,reproducibility,and interpretability of features,and the generalizability and interpretability of models.Finally,we offer possible solutions to current challenges in radiomics research.
基金supported in part by the National Key R&D Program of China(No.2022YFB3904503)National Natural Science Foundation of China(No.62172418)。
文摘To solve the problem of poor detection and limited application range of current intrusion detection methods,this paper attempts to use deep learning neural network technology to study a new type of intrusion detection method.Hence,we proposed an intrusion detection algorithm based on convolutional neural network(CNN)and AdaBoost algorithm.This algorithm uses CNN to extract the characteristics of network traffic data,which is particularly suitable for the analysis of continuous and classified attack data.The AdaBoost algorithm is used to classify network attack data that improved the detection effect of unbalanced data classification.We adopt the UNSW-NB15 dataset to test of this algorithm in the PyCharm environment.The results show that the detection rate of algorithm is99.27%and the false positive rate is lower than 0.98%.Comparative analysis shows that this algorithm has advantages over existing methods in terms of detection rate and false positive rate for small proportion of attack data.
文摘A large number of network security breaches in IoT networks have demonstrated the unreliability of current Network Intrusion Detection Systems(NIDSs).Consequently,network interruptions and loss of sensitive data have occurred,which led to an active research area for improving NIDS technologies.In an analysis of related works,it was observed that most researchers aim to obtain better classification results by using a set of untried combinations of Feature Reduction(FR)and Machine Learning(ML)techniques on NIDS datasets.However,these datasets are different in feature sets,attack types,and network design.Therefore,this paper aims to discover whether these techniques can be generalised across various datasets.Six ML models are utilised:a Deep Feed Forward(DFF),Convolutional Neural Network(CNN),Recurrent Neural Network(RNN),Decision Tree(DT),Logistic Regression(LR),and Naive Bayes(NB).The accuracy of three Feature Extraction(FE)algorithms is detected;Principal Component Analysis(PCA),Auto-encoder(AE),and Linear Discriminant Analysis(LDA),are evaluated using three benchmark datasets:UNSW-NB15,ToN-IoT and CSE-CIC-IDS2018.Although PCA and AE algorithms have been widely used,the determination of their optimal number of extracted dimensions has been overlooked.The results indicate that no clear FE method or ML model can achieve the best scores for all datasets.The optimal number of extracted dimensions has been identified for each dataset,and LDA degrades the performance of the ML models on two datasets.The variance is used to analyse the extracted dimensions of LDA and PCA.Finally,this paper concludes that the choice of datasets significantly alters the performance of the applied techniques.We believe that a universal(benchmark)feature set is needed to facilitate further advancement and progress of research in this field.
文摘AIM:To review recent innovations,challenges,and applications of small incision lenticule extraction(SMILE)extracted lenticule for treating ocular disorders.METHODS:A literature review was performed in the PubMed database,which was last updated on 30 December 2021.There was no limit regarding language.The authors evaluated the reference lists of the collected papers to find any relevant research.RESULTS:Due to the simplicity and accuracy of modern femtosecond lasers and the extensive development of SMILE surgery,many healthy human corneal stromal lenticules were extracted during surgery,motivating some professionals to investigate the SMILE lenticule reusability in different ocular disorders.In addition,new approaches had been developed to preserve,modify,and bioengineer the corneal stroma,leading to the optimal use of discarded byproducts such as lenticules from SMILE surgery.The lenticules can be effectively re-implanted into the autologous or allogenic corneas of human subjects to treat refractive errors,corneal ectasia,and corneal perforation and serve as a patch graft for glaucoma drainage devices with better cosmetic outcomes.CONCLUSION:SMILE-extracted lenticules could be a viable alternative to human donor corneal tissue.
基金the Science and Technology Key Project of Anhui Province,China(No.2022e03020004).
文摘Lithium recovery from spent lithium-ion batteries(LIBs)have attracted extensive attention due to the skyrocketing price of lithium.The medium-temperature carbon reduction roasting was proposed to preferential selective extraction of lithium from spent Li-CoO_(2)(LCO)cathodes to overcome the incomplete recovery and loss of lithium during the recycling process.The LCO layered structure was destroyed and lithium was completely converted into water-soluble Li2CO_(3)under a suitable temperature to control the reduced state of the cobalt oxide.The Co metal agglomerates generated during medium-temperature carbon reduction roasting were broken by wet grinding and ultrasonic crushing to release the entrained lithium.The results showed that 99.10%of the whole lithium could be recovered as Li2CO_(3)with a purity of 99.55%.This work provided a new perspective on the preferentially selective extraction of lithium from spent lithium batteries.
基金National Natural Science Foundation of China(Nos.42071444,42101444)。
文摘Cultural relics line graphic serves as a crucial form of traditional artifact information documentation,which is a simple and intuitive product with low cost of displaying compared with 3D models.Dimensionality reduction is undoubtedly necessary for line drawings.However,most existing methods for artifact drawing rely on the principles of orthographic projection that always cannot avoid angle occlusion and data overlapping while the surface of cultural relics is complex.Therefore,conformal mapping was introduced as a dimensionality reduction way to compensate for the limitation of orthographic projection.Based on the given criteria for assessing surface complexity,this paper proposed a three-dimensional feature guideline extraction method for complex cultural relic surfaces.A 2D and 3D combined factor that measured the importance of points on describing surface features,vertex weight,was designed.Then the selection threshold for feature guideline extraction was determined based on the differences between vertex weight and shape index distributions.The feasibility and stability were verified through experiments conducted on real cultural relic surface data.Results demonstrated the ability of the method to address the challenges associated with the automatic generation of line drawings for complex surfaces.The extraction method and the obtained results will be useful for line graphic drawing,displaying and propaganda of cultural relics.
基金National Natural Science Foundation of China(No.42271416)Guangxi Science and Technology Major Project(No.AA22068072)Shennongjia National Park Resources Comprehensive Investigation Research Project(No.SNJNP2023015).
文摘Timely acquisition of rescue target information is critical for emergency response after a flood disaster.Unmanned Aerial Vehicles(UAVs)equipped with remote sensing capabilities offer distinct advantages,including high-resolution imagery and exceptional mobility,making them well suited for monitoring flood extent and identifying rescue targets during floods.However,there are some challenges in interpreting rescue information in real time from flood images captured by UAVs,such as the complexity of the scenarios of UAV images,the lack of flood rescue target detection datasets and the limited real-time processing capabilities of the airborne on-board platform.Thus,we propose a real-time rescue target detection method for UAVs that is capable of efficiently delineating flood extent and identifying rescue targets(i.e.,pedestrians and vehicles trapped by floods).The proposed method achieves real-time rescue information extraction for UAV platforms by lightweight processing and fusion of flood extent extraction model and target detection model.The flood inundation range is extracted by the proposed method in real time and detects targets such as people and vehicles to be rescued based on this layer.Our experimental results demonstrate that the Intersection over Union(IoU)for flood water extraction reaches an impressive 80%,and the IoU for real-time flood water extraction stands at a commendable 76.4%.The information on flood stricken targets extracted by this method in real time can be used for flood emergency rescue.
基金financially supported by the National Natural Science Foundation of China(No.52072322)the Department of Science and Technology of Sichuan Province,China(Nos.23GJHZ0147,23ZDYF0262,2022YFG0294,and 2019-GH02-00052-HZ)。
文摘Electrochemical lithium extraction from salt lakes is an effective strategy for obtaining lithium at a low cost.Nevertheless,the elevated Mg:Li ratio and the presence of numerous coexisting ions in salt lake brines give rise to challenges,such as prolonged lithium extraction periods,diminished lithium extraction efficiency,and considerable environmental pollution.In this work,Li FePO4(LFP)served as the electrode material for electrochemical lithium extraction.The conductive network in the LFP electrode was optimized by adjusting the type of conductive agent.This approach resulted in high lithium extraction efficiency and extended cycle life.When the single conductive agent of acetylene black(AB)or multiwalled carbon nanotubes(MWCNTs)was replaced with the mixed conductive agent of AB/MWCNTs,the average diffusion coefficient of Li+in the electrode increased from 2.35×10^(-9)or 1.77×10^(-9)to 4.21×10^(-9)cm^(2)·s^(-1).At the current density of 20 mA·g^(-1),the average lithium extraction capacity per gram of LFP electrode increased from 30.36 mg with the single conductive agent(AB)to 35.62 mg with the mixed conductive agent(AB/MWCNTs).When the mixed conductive agent was used,the capacity retention of the electrode after 30 cycles reached 82.9%,which was considerably higher than the capacity retention of 65.8%obtained when the single AB was utilized.Meanwhile,the electrode with mixed conductive agent of AB/MWCNTs provided good cycling performance.When the conductive agent content decreased or the loading capacity increased,the electrode containing the mixed conductive agent continued to show excellent electrochemical performance.Furthermore,a self-designed,highly efficient,continuous lithium extraction device was constructed.The electrode utilizing the AB/MWCNT mixed conductive agent maintained excellent adsorption capacity and cycling performance in this device.This work provides a new perspective for the electrochemical extraction of lithium using LFP electrodes.
基金the Horizon Europe Project“Batteries reuse and direct production of high performances cathodic and anodic materials and other raw materials from batteries recycling using low cost and environmentally friendly technologies” (RHINOCEROS project,grant no.101069685)。
文摘Lithium recovery from end-of-life Li-ion batteries(LIBs)through pyro-and hydrometallurgical recycling processes involves several refining stages,with high consumption of reagents and energy.A competitive technological alternative is the electrochemical oxidation of the cathode materials,whereby lithium can be deintercalated and transferred to an electrolyte solution without the aid of chemical extracting compounds.This article investigates the potential to selectively recover Li from LIB cathode materials by direct electrochemical extraction in aqueous solutions.The process allowed to recovering up to 98%of Li from high-purity commercial cathode materials(LiMn_(2)O_(4),LiCoO_(2),and Li Ni_(1/3)Mn_(1/3)Co_(1/3)O_(2))with a faradaic efficiency of 98%and negligible co-extraction of Co,Ni,and Mn.The process was then applied to recover Li from the real waste LIBs black mass obtained by the physical treatment of electric vehicle battery packs.This black mass contained graphite,conductive carbon,and metal impurities from current collectors and steel cases,which significantly influenced the evolution and performances of Li electrochemical extraction.Particularly,due to concomitant oxidation of impurities,lithium extraction yields and faradaic efficiencies were lower than those obtained with high-purity cathode materials.Copper oxidation was found to occur within the voltage range investigated,but it could not quantitatively explain the reduced Li extraction performances.In fact,a detailed investigation revealed that above 1.3 V vs.Ag/Ag Cl,conductive carbon can be oxidized,contributing to the decreased Li extraction.Based on the reported experimental results,guidelines were provided that quantitatively enable the extraction of Li from the black mass,while preventing the simultaneous oxidation of impurities and,consequently,reducing the energy consumption of the proposed Li recovery method.
文摘Purpose:The purpose of this study is to serve as a comprehensive review of the existing annotated corpora.This review study aims to provide information on the existing annotated corpora for event extraction,which are limited but essential for training and improving the existing event extraction algorithms.In addition to the primary goal of this study,it provides guidelines for preparing an annotated corpus and suggests suitable tools for the annotation task.Design/methodology/approach:This study employs an analytical approach to examine available corpus that is suitable for event extraction tasks.It offers an in-depth analysis of existing event extraction corpora and provides systematic guidelines for researchers to develop accurate,high-quality corpora.This ensures the reliability of the created corpus and its suitability for training machine learning algorithms.Findings:Our exploration reveals a scarcity of annotated corpora for event extraction tasks.In particular,the English corpora are mainly focused on the biomedical and general domains.Despite the issue of annotated corpora scarcity,there are several high-quality corpora available and widely used as benchmark datasets.However,access to some of these corpora might be limited owing to closed-access policies or discontinued maintenance after being initially released,rendering them inaccessible owing to broken links.Therefore,this study documents the available corpora for event extraction tasks.Research limitations:Our study focuses only on well-known corpora available in English and Chinese.Nevertheless,this study places a strong emphasis on the English corpora due to its status as a global lingua franca,making it widely understood compared to other languages.Practical implications:We genuinely believe that this study provides valuable knowledge that can serve as a guiding framework for preparing and accurately annotating events from text corpora.It provides comprehensive guidelines for researchers to improve the quality of corpus annotations,especially for event extraction tasks across various domains.Originality/value:This study comprehensively compiled information on the existing annotated corpora for event extraction tasks and provided preparation guidelines.