This study investigates the properties of high-purity starches extracted from Polygonum multiflorum(PMS)and Smilax glabra(SGS).The starches were characterized by scanning electron microscopy,Fouriertransform infrared ...This study investigates the properties of high-purity starches extracted from Polygonum multiflorum(PMS)and Smilax glabra(SGS).The starches were characterized by scanning electron microscopy,Fouriertransform infrared spectroscopy,X-ray diffraction,high-performance anion-exchange chromatography,and differential scanning calorimetry.Significant differences were observed in their morphological,physicochemical,and functional properties.PMS had a smaller particle size(13.68 μm),irregular polygonal shape,A-type,lower water absorption(62.67 %),and higher oil absorption(51.17 %).In contrast,SGS exhibited larger particles(31.75 μm),a nearly spherical shape,B-type,higher crystallinity(50.66 %),and greater amylose content(21.54 %),with superior thermal stability,shear resistance,and gelatinization enthalpy.SGS also contained higher resistant starch(83.28 %) and longer average chain length(20.58 %),but showed lower solubility,swelling power,light transmittance,and freeze-thaw stability.The physicochemical properties differences in crystal pattern and particle morphology between PMS and SGS lead to distinct behaviors during in vitro digestion and fermentation.These findings highlight the potential of medicinal plant starches in functional ingredients and industrial processes.展开更多
Standard bacterial suspensions play a crucial role in microbiological diagnosis.Traditional prepar-ation methods,which rely heavily on manual operations,face challenges such as poor reproducibility,low ef-ficiency,and...Standard bacterial suspensions play a crucial role in microbiological diagnosis.Traditional prepar-ation methods,which rely heavily on manual operations,face challenges such as poor reproducibility,low ef-ficiency,and biosafety concerns.In this study,we propose a high-precision automated colony extraction and separation system that combines large-field imaging and artificial intelligence(AI)to facilitate intelligent screening and localization of colonies.Firstly,a large-field imaging system was developed to capture high-resolution images of 90 mm Petri dishes,achieving a physical resolution of 13.2μm and an imaging speed of 13 frames per second.Subsequently,AI technology was employed for the automatic recognition and localiza-tion of colonies,enabling the selection of target colonies with diameters ranging from 1.9 to 2.3 mm.Next,a three-axis motion control platform was designed,accompanied by a path planning algorithm for the efficient extraction of colonies.An electronic pipette was employed for accurate colony collection.Additionally,a bacterial suspension concentration measurement module was developed,incorporating a 650 nm laser diode as the light source,achieving a measurement accuracy of 0.01 McFarland concentration(MCF).Finally,the system’s performance was validated through the preparation of an Esckerichia coli(E.coli)suspension.After 17 hours of cultivation,E.coli was extracted four times,achieving the target concentration set by the system.This work is expected to enable rapid and accurate microbial sample preparation,significantly reducing de-tection cycles and alleviating the workload of healthcare personnel.展开更多
The efficient extraction and separation of valuable metal elements from coal gasification fine slag(CGFS)are crucial for the comprehensive high-value utilization of its constituents.This study focused on the carbon-ri...The efficient extraction and separation of valuable metal elements from coal gasification fine slag(CGFS)are crucial for the comprehensive high-value utilization of its constituents.This study focused on the carbon-rich components of CGFS(CGFS-H)and systematically investigates the selective leaching behavior of Fe^(3+),Al^(3+)and Ca^(2+)using three organic acid extractants,i.e.,citric acid,tartaric acid,and tetrasodium iminodisuccinate.Additionally,the stepwise leaching of iron,aluminum and calcium from CGFS-H is explored.The selective dissolution mechanisms of these metals by different organic acids are elucidated through X-ray diffraction(XRD),X-ray fluorescence(XRF),and scanning electron microscopy(SEM)analyses.The results indicate that tetrasodium iminodisuccinate exhibits the highest leaching selectivity for Fe^(3+),while tartaric acid demonstrateds a comparable affinity for both Fe^(3+)and Al^(3+).In contrast citric acid shows superior selectivity toward Ca^(2+).The leaching yield of Fe^(3+),Al^(3+)and Ca^(2+)after sequential leaching with the three organic acids were 79.8%,65.08%and 78.6%,respectively.These findings confirm that effective and selective separation of Fe^(3+),Al^(3+)and Ca^(2+)from CGFS-H can be achieved via optimized organic acid-based leaching strategies.This advancement provides a critical foundation for developing Ca/Fe/Al hydrotalcite materials using CGFS-H as a sustainable feedstock,thereby facilitating the transformation of waste residue into high-value functional materials and promoting resourceefficient utilization of coal gasification fine slag.展开更多
A reversed-phase high-performance liquid chromatography(HPLC)method was developed for the direct determination of docosahexaenoic acid(DHA)in sturgeon caviar extract.The assay employed n-hexane extraction combined wit...A reversed-phase high-performance liquid chromatography(HPLC)method was developed for the direct determination of docosahexaenoic acid(DHA)in sturgeon caviar extract.The assay employed n-hexane extraction combined with gradient elution(ZORBAX SB-C18 column),with data collected using a diode array detector.The content was calculated by external standard method and validated against the national standard(GB 5009.168-2016).The study also measured DPPH free radical scavenging capacity and moisture retention rate across different DHA concentration groups.The results demonstrate that the proposed method exhibits excellent linearity(r=0.9997),with recovery rates ranging from 92.1% to 101.1% and relative standard deviations(RSD)of 2.23% to 3.92%.Compared to the national standard method,the relative deviation was 0.67% to 1.68%.At specific test concentrations,the high-DHA group shows significantly higher moisture retention(100.48%),hygroscopicity(100.85%),and DPPH scavenging efficiency(57.46%)than the low-DHA group(10.33%,11.76%,and 3.71%).The RP-HPLC method developed in this study simplifies DHA detection procedures with simple reagents and reliable results,making it suitable for rapid qualitative identification and quantitative analysis of target components in caviar extract quality control.The DPPH experiment further reveals the correlation between DHA content and antioxidant efficacy in sturgeon caviar extracts,providing scientific evidence for developing functional cosmetics.展开更多
Diesel accounts for over 60%of the products derived from direct coal liquefaction(DCL).Compared to petroleum-based diesel,DCL diesel exhibits a cetane number ranging from 30 to 40,which fails to meet the automotive di...Diesel accounts for over 60%of the products derived from direct coal liquefaction(DCL).Compared to petroleum-based diesel,DCL diesel exhibits a cetane number ranging from 30 to 40,which fails to meet the automotive diesel standard requirement of≥45.Therefore,rapid and accurate analysis of its chemical composition is crucial for property optimization to meet fuel specifications by component blending.Thought traditional methods like gas chromatography offer high accuracy,they are unsuitable for rapid online analysis under industrial conditions.Near-infrared(NIR)spectroscopy can provide advantages in rapid,non-destructive analysis.Its application however,is limited by the complexity of spectral data interpretation.Machine learning(ML)is effective method for extracting valuable information from spectra and establishing high-precision prediction models.This study integrates NIR spectroscopy with ML to construct a spectral-composition database for DCL diesel.Feature extraction was performed using the correlation coefficient and mutual information methods to screen key wavelength variables and reduce data dimensionality.Subsequently,the predictive performance of three ML models—Lasso,SVR and XGBoost—was compared.Results indicate that excluding spectral data with absorbance greater than 1 significantly enhances model accuracy,increasing the test set R^(2) from 0.85 to 0.96.After feature extraction,the optimal number of wavelength variables was reduced to 177,substantially improving computational efficiency.Among the models evaluated,the SVR-MI-0.9 model,based on mutual information feature selection,demonstrated the best performance,achieving training and test set R^(2) values both exceeding 0.98.This model enables precise prediction of paraffin,naphthene,and aromatic hydrocarbon contents.This research provides a robust methodology for intelligent online quality monitoring.An intelligent NIR spectroscopy data analysis software was independently developed based on the established model.Compared with comprehensive two-dimensional gas chromatography,the software reduced the analysis time by over 98%,with an absolute prediction error below 0.2%.Thus,rapid analysis of DCL diesel components was successfully realized.展开更多
Vetiver(Vetiveria zizanioides)is often extracted as essential oils used in cosmetics,but there are few indepth reports on its cosmetic and skincare efficacy.In order to explore the neuro-cosmetic activity of vetiver e...Vetiver(Vetiveria zizanioides)is often extracted as essential oils used in cosmetics,but there are few indepth reports on its cosmetic and skincare efficacy.In order to explore the neuro-cosmetic activity of vetiver extract,ELISA and Griess methods were used to detect the secretion levels of related neural and inflammatory mediators,and TRPV1 activity was analyzed by fluorescence staining in this study.The results shows that in vitro cell models,1%vetiver extract decreases cortisol production by 25.8%and increases beta-endorphin secretion by 287.9%when the calcium influx induced by TRPV1 activation is blocked and the inhibitory rate is 22.9%.And 2%vetiver extract decreases the levels of NO,TNF-αand IL-6 when the inhibition rates are 86.3%,69.4%and 81.8%,respectively.Therefore,vetiver extract can effectively combat skin stress,relieve skin discomfort caused by inflammation and nerve sensitivity,thus providing a feeling of well-being.The vetiver extract has skincare benefits at the neurological level which shows potential for neuro-cosmetic application.展开更多
N,N,N',N'-tetraoctyl diglycolamide(TODGA)is a potential extractant for the co-extraction of lanthanides and actinides in high-level liquid waste.In this study,the radiolysis and extraction properties of TODGA ...N,N,N',N'-tetraoctyl diglycolamide(TODGA)is a potential extractant for the co-extraction of lanthanides and actinides in high-level liquid waste.In this study,the radiolysis and extraction properties of TODGA in kerosene solvents contacted with the aqueous phase of varying HNO_(3) concentrations were systematically investigated,and the complexation mechanism was analyzed in conjunction with density functional theory(DFT)calculations.After γ-irradiation,the variation of TODGA concentration was detected,and the variation trends in the relative content of radiolysis products(RPs)with sample type and absorbed dose were demonstrated.Results indicated that the breaking of the amide bond,ether bond,and C_(amide)-C_(ether)bond was the primary radiolysis routes.The aqueous-phase precipitate was studied as a potential new mode of TODGA radiolysis in ultrapure water aqueous phase.Moreover,TODGA/kerosene exhibited excellent extraction capabilities for lanthanides even after absorbing 100 kGy,and HNO_(3) can maintain a portion of TODGA's extraction capacity.The DFT method was applied to calculate and evaluate the complexing ability of TODGA and some of its RPs toward lanthanides.The results revealed that the complexing ability of TODGA for Ce(Ⅲ),Eu(Ⅲ),and Dy(Ⅲ)was enhanced successively,and the complexing ability of the RPs with intact oxygen-containing structures could not be neglected.展开更多
In this study,we developed a novel bilayered scaffold consisting of a bottom layer composed of the Decellularized Bovine Pericardium(DP)coated with Polyaniline Nanoparticles(PANINPs)and a top layer made of an electros...In this study,we developed a novel bilayered scaffold consisting of a bottom layer composed of the Decellularized Bovine Pericardium(DP)coated with Polyaniline Nanoparticles(PANINPs)and a top layer made of an electrospun Poly(lactic-co-glycolic acid)/Gelatin(PLGA/Gel)membrane incorporated with Vascular Endothelial Growth Fac-tor(VEGF)and hawthorn extract.Functionally,the DP supplies native Extracellular Matrix(ECM)components and mechanical support,while PANINPs provide conductivity.The electrospun PLGA/Gel layer mimics fibrous ECM.It incorporates bioactives,with VEGF promoting pro-angiogenic stimulation and hawthorn extract enhanc-ing anticoagulant activity,as well as increasing surface hydrophilicity.The tissue adhesive ensures the interfacial integrity between the two layers.Decellularization efficiency was confirmed histologically using 4',6-diamidino-2-phenylindole(DAPI)and Hematoxylin-Eosin(H&E)staining.The DP exhibited a DNA content of 115.9±47.8 ng/mg DNA,compared to 982.88±395.42 ng/mg in Native Pericardium(NP).The PANINPs had an average par-ticle size of 104.94±13.7 nm.The conductivity of PANINPs-coated decellularized pericardium was measured to be 9.093±8.6×10-4 S/cm using the four-point probe method.PLGA/Gel membranes containing hawthorn extract(1%,5%,10%,and 15%w/v)and VEGF(0.1μg/mL,0.5μg/mL,and 1μg/mL)were fabricated by electrospinning,result-ing in fiber diameters between 850 and 1200 nm and pore sizes between 14 and 20μm.The anticoagulant efficiency of the membranes containing hawthorn extract reached 430 s in the Activated Partial Thromboplastin Time Assay(aPTT).Mechanical testing revealed a tensile strength of 22.70±6.33 MPa,an elongation of 53.58±10.63%,and Young's modulus of 0.67±0.10 MPa.The scaffold also exhibited over 91%cell viability and excellent cardiomyo-cyte adhesion.The hemolysis ratio was determined to be 0.421±0.191%,which confirms its blood compatibility.Our results indicate that the proposed bilayered scaffold can be a promising candidate for cardiac patch applications.展开更多
The lack of macro-continuity and mechanical strength of covalent organic frameworks(COFs)has significantly limited their practical applications.Here,we propose an“alcohol-triggered defect cleavage”strategy to precis...The lack of macro-continuity and mechanical strength of covalent organic frameworks(COFs)has significantly limited their practical applications.Here,we propose an“alcohol-triggered defect cleavage”strategy to precisely regulate the growth and stacking of COF grains through a moderate reversed Schiff base reaction,realizing the direct synthesis of COF nanofibers(CNFs)with high aspect ratio(L/D=103.05)and long length(>20μm).An individual CNF exhibits a biomimetic scale-like architecture,achieving superior flexibility and fatigue resistance under dynamic bending via a multiscale stress dissipation mechanism.Taking advantages of these structural features,we engineer CNF aerogels(CNF-As)with programmable porous structures(e.g.,honeycomb,lamellar,isotropic)via directional ice-template methodology.CNF-As demonstrate 100%COF content,high specific surface area(396.15 m^(2)g^(-1))and superelasticity(~0%elastic deformation after 500 compression cycles at 50%strain),outperforming most COF-based counterparts.Compared with the conventional COF aerogels,the unique structural features of CNF-A enable it to perform outstandingly in uranium extraction,with an 11.72-fold increment in adsorption capacity(920.12 mg g^(-1))and adsorption rate(89.9%),and a 2.48-fold improvement in selectivity(U/V=2.31).This study provides a direct strategy for the development of next-generation COF materials with outstanding functionality and structural robustness.展开更多
Peony root bark extract as was used the research object,and used a series of biochemical and cellular experiments to investigate its whitening,anti-inflammatory,oil control,acne,and inhibition of the growth of Malasse...Peony root bark extract as was used the research object,and used a series of biochemical and cellular experiments to investigate its whitening,anti-inflammatory,oil control,acne,and inhibition of the growth of Malassezia.The results showed that the inhibition rate of melanin synthesis was significantly increased to 86.43%at a concentration of 2.0%;the secretion of inflammatory factors IL-1αand IL-6 by macrophages(RAW264.7)was significantly reduced to 4.94 pg/mL and 6.42 pg/mL,respectively;the fluorescence signal of Nile red in sebaceous gland cells(SZ95)was significantly reduced to 57.5%;the inhibition rate of Propionibacterium acnes was 37.7%for 20 min of action;and the average inhibition rate of Malassezia marcescens was 78.1%for 20 min of action.Thus,it can be seen that the peony root bark extract has multiple skin-care effects and is a natural and healthy cosmetic plant raw material,which provides a solid theoretical basis for its application in cosmetics.展开更多
As an important class of phenanthroline derivatives containing soft N and hard O donor atoms,the laborious syntheses of unsymmetrical 1,10-phenanthroline-derived diamide ligands(DAPhen) have hindered its extensive stu...As an important class of phenanthroline derivatives containing soft N and hard O donor atoms,the laborious syntheses of unsymmetrical 1,10-phenanthroline-derived diamide ligands(DAPhen) have hindered its extensive study.In this work,we first report a convenient synthetic method for the construction of DAPhen using Friedländer reaction by two facile steps(vs.previous 12 steps).A variety of DAPhen ligands are readily available,especially unsymmetrical ones,which give us a platform to systematically study the substituent effect on f-block elements extraction performance.The performance of unsymmetrical extractants is experimentally confirmed to falls between that of their corresponding symmetrical extractants by extracting UO_(2)^(2+) as the representative f-block element.This work provides a direct and versatile method to synthesize symmetrical and unsymmetrical DAPhen,which paves way for the investigations on their coordination properties with metal ions and other applications.展开更多
Text semantic extraction has been envisioned as a promising solution to improve the data transmission efficiency with the limited radio resources for the autonomous interactions among machines and things in the future...Text semantic extraction has been envisioned as a promising solution to improve the data transmission efficiency with the limited radio resources for the autonomous interactions among machines and things in the future sixth-generation(6G)wireless networks.In this paper,we propose a Chinese text semantic extraction model,namely T-Pointer,to improve the quality of semantic extraction by integrating the Transformer with the pointer-generator network.The proposed T-Pointer model consists of a semantic encoder and a semantic decoder.In the encoding stage,we use the multi-head attention mechanism of the Transformer to extract semantic features from the input Chinese text.In the decoding stage,we first use the Transformer to extract multi-level global text features.Then,we introduce the pointer-generator network model to directly copy the keyword information from the source text.The simulation results demonstrate that the T-Pointer model can improve the bilingual evaluation understudy(BLEU)and recalloriented understudy for gisting evaluation(ROUGE)by 14.69%and 14.87%on average in comparison with the state-of-the-art models,respectively.Also,we implement the T-Pointer model on a semantic communication system based on the universal software radio peripheral(USRP)platform.The result shows that the packet delay of semantic transmission can be reduced by 52.05%on average,compared to traditional information transmission.展开更多
This article presents a new synergistic extraction system composed of Cyanex 272(C272,bis(2,4,4-trimethylpentyl)phosphinic acid)and iso-octanol for Sc_(3+) separation.The proposed synergistic system possessed an Sc^(3...This article presents a new synergistic extraction system composed of Cyanex 272(C272,bis(2,4,4-trimethylpentyl)phosphinic acid)and iso-octanol for Sc_(3+) separation.The proposed synergistic system possessed an Sc^(3+) extraction efficiency of 93.5%and a back-extraction efficiency of 82.7%,with selectivity coefficients of β_(Sc/Fe)=459 and β_(Sc/Al)=4241,which are considerably higher as compared to the current extraction systems.The extraction mechanism was studied and interpreted.The enhanced extraction efficiency is attributed to the increased hydrophobicity of the ternary complex,whereas the back-extraction efficiency can be ascribed to the attenuated stability of the complex.C272 and C272–iso-octanol systems also possess considerable surface activity,which is beneficial for the phase separation in solvent extraction.Based on the solvent extraction results,a preliminary study was conducted on polymer inclusion membranes(PIMs)using the binary system for Sc^(3+) separation to avoid the formation of the third phase,achieving an optimal initial flux of PIM of 6.71×10^(−4)mol·m^(−2)·h^(−1).Our results provide valuable information on highly efficient Sc^(3+) separation,and the study on PIM extraction has shown a green alternative to solvent extraction.展开更多
Chamaedorea seifrizii is a bamboo plant that is mainly used for its air-purifying properties and ornamental value.Due to the scarcity of reports on its phytochemical constitutes,this study was aimed at chemical profil...Chamaedorea seifrizii is a bamboo plant that is mainly used for its air-purifying properties and ornamental value.Due to the scarcity of reports on its phytochemical constitutes,this study was aimed at chemical profiling,phytochemical analysis and evaluation of its in-vitro biological activities of acetone extracts of auxiliary inflorescence and fruits of Chamaedorea seifrizii accompanied by in-silico analysis.Standard techniques were employed for phytochemical screening of phenolics,flavonoids and tannins and anti-oxidant and anti-inflammatory tests.In-silico analysis coupled with molecular dynamics simulation was also conducted to find out interaction of some components to inflammatory responses.Bioactive compounds in auxiliary inflorescence and fruit extracts were studied using a gas chromatography-flame ionization detector(GC-FID).Numerous antioxidant tests were carried out,including those for 2,2-diphenyl-1-picrylhydrazyl(DPPH),hydroxyl radicals,and nitric oxide radicals and shown that all both extracts depicted exorbitant levels of activities with values ranging from 48 to 96%.Results of GC-FID revealed maximum 18-22 constituents in acetone fractions with phenethyl cinnamate and hinokione as predominant components in auxiliary inflorescence and fruits,respectively.In addition,a strong anti-inflammatory activity was observed with acetone containing extracts.In-silico analysis validated the interaction of phytocomponents to inflammation initiation enzymes.Phytochemicals found in Chamaedorea seifrizii extracts may have pharmacological,antioxidant and anti-inflammatory properties.Chamaedorea seifrizii may be used in this study to produce new herbal remedies for a range of illnesses,perhaps resulting in the development of novel drugs.展开更多
The extraction of uranium from seawater via membrane adsorption is a promising strategy for ensuring a long-term supply of uranium and the sustainability of nuclear energy.However,this approach has been hindered by th...The extraction of uranium from seawater via membrane adsorption is a promising strategy for ensuring a long-term supply of uranium and the sustainability of nuclear energy.However,this approach has been hindered by the longstanding challenge of identifying sustainable membrane materials.In response,we propose a prototypal hybridization strategy to design a novel series of aminated conjugated microporous polymer(CMPN)@collagen fiber membrane(COLM).These sustainable and low-cost membrane materials allow a rapid and high-affinity kinetic to capture 90%of the uranium in just 30 min from 50 ppm with a high selectivity of Kd>105 mL·g^(−1).They also afford a robustly reusable adsorption capacity as high as 345 mg·g^(−1)that could harvest 1.61 mg·g^(−1)of uranium in a short 7-day real marine engineering in Fujian Province,even though suffered from very low uranium concentration of 3.29μg·L^(−1)and tough influence of salts such as 10.77 g·L^(−1)of Na^(+),1.75μg·L^(−1)of VO_(3)^(−)etc.in the rough seas.The structural evidence from both experimental and theoretical studies confirmed the formation of favorable chelating motifs from the amino group on CMPN-COLM,and the intensification by the synergistic effect from the size-sieving action of CMPN and the capillary inflow effect of COLM.展开更多
The leaching process and kinetic behavior of lepidolite in hydrochloric acid were explored systematically.The influence of leaching conditions on the leaching efficiency of valuable metals in lepidolite was investigat...The leaching process and kinetic behavior of lepidolite in hydrochloric acid were explored systematically.The influence of leaching conditions on the leaching efficiency of valuable metals in lepidolite was investigated.Under optimized conditions,the leaching efficiencies of Li,K,Rb,Cs and Al are 92.02%,93.31%,88.59%,86.75%and 81.07%,respectively.Kinetics research results show that the leaching process conforms to the shrinking core model that is under the mixed control of chemical reaction and diffusion through the solid product layer.In addition,the contribution of solid product layer diffusion to the leaching gradually expands as the temperature rises,but it is still significantly less than the contribution of chemical reaction.Cost saving in the neutralizing agent and leaching processes makes hydrochloric acid an economical leaching agent for lepidolite.Finally,the Li2CO3 product with a purity of 99.89%was synthesized from the hydrochloric acid leachate.展开更多
Objective:To investigate the effect of a water-soluble nacre extract derived from Pinctada fucata on skeletal muscle aging.Methods:Naturally aged C57BL/6J mice received nacre extract mixed in chow for 12 weeks.Forelim...Objective:To investigate the effect of a water-soluble nacre extract derived from Pinctada fucata on skeletal muscle aging.Methods:Naturally aged C57BL/6J mice received nacre extract mixed in chow for 12 weeks.Forelimb grip strength,hanging performance,and locomotor activity were assessed.Skeletal muscle remodeling and signaling were evaluated by histology and immunostaining for fibrosis,contractile-marker features,senescence-and DNA damage-associated markers,inflammatory signaling,and mitochondrial proteins.Oxidative status was assessed by determining antioxidant capacity,lipid peroxidation,and oxidative DNA damage.Transcriptomic profiling was also performed,and selected targets were validated by quantitative RT-PCR and immunostaining.In addition,differentiated C2C12 myotubes were exposed to doxorubicin and treated with nacre extract;senescence-associated β-galactosidase,DNA damage signaling,and cell viability were measured.Results:Nacre extract increased forelimb grip strength and showed a positive trend in hanging performance without altering spontaneous locomotion.It also reduced collagen deposition,preserved contractile-marker immunoreactivity,attenuated senescence-and inflammation-associated signals,and increased mitochondrial protein immunoreactivity.Oxidative DNA damage was notably reduced by nacre extract.Transcriptomics indicated modulation of stress/redox programs and increased neurotrophic tyrosine kinase receptor type 2 expression,which were supported by tissue-level validation.In C2C12 myotubes,nacre extract suppressed doxorubicin-induced senescence-associated phenotypes without loss of cell viability.Conclusions:Water-soluble nacre extract mitigates skeletal muscle aging through coordinated modulation of oxidative stress,inflammation,mitochondrial features,and cellular senescence.展开更多
Deep learning has made significant progress in the field of oriented object detection for remote sensing images.However,existing methods still face challenges when dealing with difficult tasks such as multi-scale targ...Deep learning has made significant progress in the field of oriented object detection for remote sensing images.However,existing methods still face challenges when dealing with difficult tasks such as multi-scale targets,complex backgrounds,and small objects in remote sensing.Maintaining model lightweight to address resource constraints in remote sensing scenarios while improving task completion for remote sensing tasks remains a research hotspot.Therefore,we propose an enhanced multi-scale feature extraction lightweight network EM-YOLO based on the YOLOv8s architecture,specifically optimized for the characteristics of large target scale variations,diverse orientations,and numerous small objects in remote sensing images.Our innovations lie in two main aspects:First,a dynamic snake convolution(DSC)is introduced into the backbone network to enhance the model’s feature extraction capability for oriented targets.Second,an innovative focusing-diffusion module is designed in the feature fusion neck to effectively integrate multi-scale feature information.Finally,we introduce Layer-Adaptive Sparsity for magnitude-based Pruning(LASP)method to perform lightweight network pruning to better complete tasks in resource-constrained scenarios.Experimental results on the lightweight platform Orin demonstrate that the proposed method significantly outperforms the original YOLOv8s model in oriented remote sensing object detection tasks,and achieves comparable or superior performance to state-of-the-art methods on three authoritative remote sensing datasets(DOTA v1.0,DOTA v1.5,and HRSC2016).展开更多
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
Although Named Entity Recognition(NER)in cybersecurity has historically concentrated on threat intelligence,vital security data can be found in a variety of sources,such as open-source intelligence and unprocessed too...Although Named Entity Recognition(NER)in cybersecurity has historically concentrated on threat intelligence,vital security data can be found in a variety of sources,such as open-source intelligence and unprocessed tool outputs.When dealing with technical language,the coexistence of structured and unstructured data poses serious issues for traditional BERT-based techniques.We introduce a three-phase approach for improved NER inmulti-source cybersecurity data that makes use of large language models(LLMs).To ensure thorough entity coverage,our method starts with an identification module that uses dynamic prompting techniques.To lessen hallucinations,the extraction module uses confidence-based self-assessment and cross-checking using regex validation.The tagging module links to knowledge bases for contextual validation and uses SecureBERT in conjunction with conditional random fields to detect entity boundaries precisely.Our framework creates efficient natural language segments by utilizing decoderbased LLMs with 10B parameters.When compared to baseline SecureBERT implementations,evaluation across four cybersecurity data sources shows notable gains,with a 9.4%–25.21%greater recall and a 6.38%–17.3%better F1-score.Our refined model matches larger models and achieves 2.6%–4.9%better F1-score for technical phrase recognition than the state-of-the-art alternatives Claude 3.5 Sonnet,Llama3-8B,and Mixtral-7B.The three-stage architecture identification-extraction-tagging pipeline tackles important cybersecurity NER issues.Through effective architectures,these developments preserve deployability while setting a new standard for entity extraction in challenging security scenarios.The findings show how specific enhancements in hybrid recognition,validation procedures,and prompt engineering raise NER performance above monolithic LLM approaches in cybersecurity applications,especially for technical entity extraction fromheterogeneous sourceswhere conventional techniques fall short.Because of itsmodular nature,the framework can be upgraded at the component level as new methods are developed.展开更多
基金supported by the National Natural Science Foundation of China (No.82174074)。
文摘This study investigates the properties of high-purity starches extracted from Polygonum multiflorum(PMS)and Smilax glabra(SGS).The starches were characterized by scanning electron microscopy,Fouriertransform infrared spectroscopy,X-ray diffraction,high-performance anion-exchange chromatography,and differential scanning calorimetry.Significant differences were observed in their morphological,physicochemical,and functional properties.PMS had a smaller particle size(13.68 μm),irregular polygonal shape,A-type,lower water absorption(62.67 %),and higher oil absorption(51.17 %).In contrast,SGS exhibited larger particles(31.75 μm),a nearly spherical shape,B-type,higher crystallinity(50.66 %),and greater amylose content(21.54 %),with superior thermal stability,shear resistance,and gelatinization enthalpy.SGS also contained higher resistant starch(83.28 %) and longer average chain length(20.58 %),but showed lower solubility,swelling power,light transmittance,and freeze-thaw stability.The physicochemical properties differences in crystal pattern and particle morphology between PMS and SGS lead to distinct behaviors during in vitro digestion and fermentation.These findings highlight the potential of medicinal plant starches in functional ingredients and industrial processes.
文摘Standard bacterial suspensions play a crucial role in microbiological diagnosis.Traditional prepar-ation methods,which rely heavily on manual operations,face challenges such as poor reproducibility,low ef-ficiency,and biosafety concerns.In this study,we propose a high-precision automated colony extraction and separation system that combines large-field imaging and artificial intelligence(AI)to facilitate intelligent screening and localization of colonies.Firstly,a large-field imaging system was developed to capture high-resolution images of 90 mm Petri dishes,achieving a physical resolution of 13.2μm and an imaging speed of 13 frames per second.Subsequently,AI technology was employed for the automatic recognition and localiza-tion of colonies,enabling the selection of target colonies with diameters ranging from 1.9 to 2.3 mm.Next,a three-axis motion control platform was designed,accompanied by a path planning algorithm for the efficient extraction of colonies.An electronic pipette was employed for accurate colony collection.Additionally,a bacterial suspension concentration measurement module was developed,incorporating a 650 nm laser diode as the light source,achieving a measurement accuracy of 0.01 McFarland concentration(MCF).Finally,the system’s performance was validated through the preparation of an Esckerichia coli(E.coli)suspension.After 17 hours of cultivation,E.coli was extracted four times,achieving the target concentration set by the system.This work is expected to enable rapid and accurate microbial sample preparation,significantly reducing de-tection cycles and alleviating the workload of healthcare personnel.
基金Supported by National Natural Science Foundation(52374279)。
文摘The efficient extraction and separation of valuable metal elements from coal gasification fine slag(CGFS)are crucial for the comprehensive high-value utilization of its constituents.This study focused on the carbon-rich components of CGFS(CGFS-H)and systematically investigates the selective leaching behavior of Fe^(3+),Al^(3+)and Ca^(2+)using three organic acid extractants,i.e.,citric acid,tartaric acid,and tetrasodium iminodisuccinate.Additionally,the stepwise leaching of iron,aluminum and calcium from CGFS-H is explored.The selective dissolution mechanisms of these metals by different organic acids are elucidated through X-ray diffraction(XRD),X-ray fluorescence(XRF),and scanning electron microscopy(SEM)analyses.The results indicate that tetrasodium iminodisuccinate exhibits the highest leaching selectivity for Fe^(3+),while tartaric acid demonstrateds a comparable affinity for both Fe^(3+)and Al^(3+).In contrast citric acid shows superior selectivity toward Ca^(2+).The leaching yield of Fe^(3+),Al^(3+)and Ca^(2+)after sequential leaching with the three organic acids were 79.8%,65.08%and 78.6%,respectively.These findings confirm that effective and selective separation of Fe^(3+),Al^(3+)and Ca^(2+)from CGFS-H can be achieved via optimized organic acid-based leaching strategies.This advancement provides a critical foundation for developing Ca/Fe/Al hydrotalcite materials using CGFS-H as a sustainable feedstock,thereby facilitating the transformation of waste residue into high-value functional materials and promoting resourceefficient utilization of coal gasification fine slag.
文摘A reversed-phase high-performance liquid chromatography(HPLC)method was developed for the direct determination of docosahexaenoic acid(DHA)in sturgeon caviar extract.The assay employed n-hexane extraction combined with gradient elution(ZORBAX SB-C18 column),with data collected using a diode array detector.The content was calculated by external standard method and validated against the national standard(GB 5009.168-2016).The study also measured DPPH free radical scavenging capacity and moisture retention rate across different DHA concentration groups.The results demonstrate that the proposed method exhibits excellent linearity(r=0.9997),with recovery rates ranging from 92.1% to 101.1% and relative standard deviations(RSD)of 2.23% to 3.92%.Compared to the national standard method,the relative deviation was 0.67% to 1.68%.At specific test concentrations,the high-DHA group shows significantly higher moisture retention(100.48%),hygroscopicity(100.85%),and DPPH scavenging efficiency(57.46%)than the low-DHA group(10.33%,11.76%,and 3.71%).The RP-HPLC method developed in this study simplifies DHA detection procedures with simple reagents and reliable results,making it suitable for rapid qualitative identification and quantitative analysis of target components in caviar extract quality control.The DPPH experiment further reveals the correlation between DHA content and antioxidant efficacy in sturgeon caviar extracts,providing scientific evidence for developing functional cosmetics.
基金Supported by National Natural Science Foundation of China(U24B6018,22178243)。
文摘Diesel accounts for over 60%of the products derived from direct coal liquefaction(DCL).Compared to petroleum-based diesel,DCL diesel exhibits a cetane number ranging from 30 to 40,which fails to meet the automotive diesel standard requirement of≥45.Therefore,rapid and accurate analysis of its chemical composition is crucial for property optimization to meet fuel specifications by component blending.Thought traditional methods like gas chromatography offer high accuracy,they are unsuitable for rapid online analysis under industrial conditions.Near-infrared(NIR)spectroscopy can provide advantages in rapid,non-destructive analysis.Its application however,is limited by the complexity of spectral data interpretation.Machine learning(ML)is effective method for extracting valuable information from spectra and establishing high-precision prediction models.This study integrates NIR spectroscopy with ML to construct a spectral-composition database for DCL diesel.Feature extraction was performed using the correlation coefficient and mutual information methods to screen key wavelength variables and reduce data dimensionality.Subsequently,the predictive performance of three ML models—Lasso,SVR and XGBoost—was compared.Results indicate that excluding spectral data with absorbance greater than 1 significantly enhances model accuracy,increasing the test set R^(2) from 0.85 to 0.96.After feature extraction,the optimal number of wavelength variables was reduced to 177,substantially improving computational efficiency.Among the models evaluated,the SVR-MI-0.9 model,based on mutual information feature selection,demonstrated the best performance,achieving training and test set R^(2) values both exceeding 0.98.This model enables precise prediction of paraffin,naphthene,and aromatic hydrocarbon contents.This research provides a robust methodology for intelligent online quality monitoring.An intelligent NIR spectroscopy data analysis software was independently developed based on the established model.Compared with comprehensive two-dimensional gas chromatography,the software reduced the analysis time by over 98%,with an absolute prediction error below 0.2%.Thus,rapid analysis of DCL diesel components was successfully realized.
文摘Vetiver(Vetiveria zizanioides)is often extracted as essential oils used in cosmetics,but there are few indepth reports on its cosmetic and skincare efficacy.In order to explore the neuro-cosmetic activity of vetiver extract,ELISA and Griess methods were used to detect the secretion levels of related neural and inflammatory mediators,and TRPV1 activity was analyzed by fluorescence staining in this study.The results shows that in vitro cell models,1%vetiver extract decreases cortisol production by 25.8%and increases beta-endorphin secretion by 287.9%when the calcium influx induced by TRPV1 activation is blocked and the inhibitory rate is 22.9%.And 2%vetiver extract decreases the levels of NO,TNF-αand IL-6 when the inhibition rates are 86.3%,69.4%and 81.8%,respectively.Therefore,vetiver extract can effectively combat skin stress,relieve skin discomfort caused by inflammation and nerve sensitivity,thus providing a feeling of well-being.The vetiver extract has skincare benefits at the neurological level which shows potential for neuro-cosmetic application.
文摘N,N,N',N'-tetraoctyl diglycolamide(TODGA)is a potential extractant for the co-extraction of lanthanides and actinides in high-level liquid waste.In this study,the radiolysis and extraction properties of TODGA in kerosene solvents contacted with the aqueous phase of varying HNO_(3) concentrations were systematically investigated,and the complexation mechanism was analyzed in conjunction with density functional theory(DFT)calculations.After γ-irradiation,the variation of TODGA concentration was detected,and the variation trends in the relative content of radiolysis products(RPs)with sample type and absorbed dose were demonstrated.Results indicated that the breaking of the amide bond,ether bond,and C_(amide)-C_(ether)bond was the primary radiolysis routes.The aqueous-phase precipitate was studied as a potential new mode of TODGA radiolysis in ultrapure water aqueous phase.Moreover,TODGA/kerosene exhibited excellent extraction capabilities for lanthanides even after absorbing 100 kGy,and HNO_(3) can maintain a portion of TODGA's extraction capacity.The DFT method was applied to calculate and evaluate the complexing ability of TODGA and some of its RPs toward lanthanides.The results revealed that the complexing ability of TODGA for Ce(Ⅲ),Eu(Ⅲ),and Dy(Ⅲ)was enhanced successively,and the complexing ability of the RPs with intact oxygen-containing structures could not be neglected.
文摘In this study,we developed a novel bilayered scaffold consisting of a bottom layer composed of the Decellularized Bovine Pericardium(DP)coated with Polyaniline Nanoparticles(PANINPs)and a top layer made of an electrospun Poly(lactic-co-glycolic acid)/Gelatin(PLGA/Gel)membrane incorporated with Vascular Endothelial Growth Fac-tor(VEGF)and hawthorn extract.Functionally,the DP supplies native Extracellular Matrix(ECM)components and mechanical support,while PANINPs provide conductivity.The electrospun PLGA/Gel layer mimics fibrous ECM.It incorporates bioactives,with VEGF promoting pro-angiogenic stimulation and hawthorn extract enhanc-ing anticoagulant activity,as well as increasing surface hydrophilicity.The tissue adhesive ensures the interfacial integrity between the two layers.Decellularization efficiency was confirmed histologically using 4',6-diamidino-2-phenylindole(DAPI)and Hematoxylin-Eosin(H&E)staining.The DP exhibited a DNA content of 115.9±47.8 ng/mg DNA,compared to 982.88±395.42 ng/mg in Native Pericardium(NP).The PANINPs had an average par-ticle size of 104.94±13.7 nm.The conductivity of PANINPs-coated decellularized pericardium was measured to be 9.093±8.6×10-4 S/cm using the four-point probe method.PLGA/Gel membranes containing hawthorn extract(1%,5%,10%,and 15%w/v)and VEGF(0.1μg/mL,0.5μg/mL,and 1μg/mL)were fabricated by electrospinning,result-ing in fiber diameters between 850 and 1200 nm and pore sizes between 14 and 20μm.The anticoagulant efficiency of the membranes containing hawthorn extract reached 430 s in the Activated Partial Thromboplastin Time Assay(aPTT).Mechanical testing revealed a tensile strength of 22.70±6.33 MPa,an elongation of 53.58±10.63%,and Young's modulus of 0.67±0.10 MPa.The scaffold also exhibited over 91%cell viability and excellent cardiomyo-cyte adhesion.The hemolysis ratio was determined to be 0.421±0.191%,which confirms its blood compatibility.Our results indicate that the proposed bilayered scaffold can be a promising candidate for cardiac patch applications.
基金supported by the National Natural Science Foundation of China(No.52403035)the Shanghai Sailing Program(23YF1400300)+1 种基金the Fundamental Research Funds for the Central Universities(2232023D-05)the Weiqiao Teaching and Research Innovation Program.
文摘The lack of macro-continuity and mechanical strength of covalent organic frameworks(COFs)has significantly limited their practical applications.Here,we propose an“alcohol-triggered defect cleavage”strategy to precisely regulate the growth and stacking of COF grains through a moderate reversed Schiff base reaction,realizing the direct synthesis of COF nanofibers(CNFs)with high aspect ratio(L/D=103.05)and long length(>20μm).An individual CNF exhibits a biomimetic scale-like architecture,achieving superior flexibility and fatigue resistance under dynamic bending via a multiscale stress dissipation mechanism.Taking advantages of these structural features,we engineer CNF aerogels(CNF-As)with programmable porous structures(e.g.,honeycomb,lamellar,isotropic)via directional ice-template methodology.CNF-As demonstrate 100%COF content,high specific surface area(396.15 m^(2)g^(-1))and superelasticity(~0%elastic deformation after 500 compression cycles at 50%strain),outperforming most COF-based counterparts.Compared with the conventional COF aerogels,the unique structural features of CNF-A enable it to perform outstandingly in uranium extraction,with an 11.72-fold increment in adsorption capacity(920.12 mg g^(-1))and adsorption rate(89.9%),and a 2.48-fold improvement in selectivity(U/V=2.31).This study provides a direct strategy for the development of next-generation COF materials with outstanding functionality and structural robustness.
文摘Peony root bark extract as was used the research object,and used a series of biochemical and cellular experiments to investigate its whitening,anti-inflammatory,oil control,acne,and inhibition of the growth of Malassezia.The results showed that the inhibition rate of melanin synthesis was significantly increased to 86.43%at a concentration of 2.0%;the secretion of inflammatory factors IL-1αand IL-6 by macrophages(RAW264.7)was significantly reduced to 4.94 pg/mL and 6.42 pg/mL,respectively;the fluorescence signal of Nile red in sebaceous gland cells(SZ95)was significantly reduced to 57.5%;the inhibition rate of Propionibacterium acnes was 37.7%for 20 min of action;and the average inhibition rate of Malassezia marcescens was 78.1%for 20 min of action.Thus,it can be seen that the peony root bark extract has multiple skin-care effects and is a natural and healthy cosmetic plant raw material,which provides a solid theoretical basis for its application in cosmetics.
基金financial support from the National Natural Science Foundation of China (Nos.22476178,U2067213)Natural Science Foundation of Zhejiang Province (No.LRG25B060002)。
文摘As an important class of phenanthroline derivatives containing soft N and hard O donor atoms,the laborious syntheses of unsymmetrical 1,10-phenanthroline-derived diamide ligands(DAPhen) have hindered its extensive study.In this work,we first report a convenient synthetic method for the construction of DAPhen using Friedländer reaction by two facile steps(vs.previous 12 steps).A variety of DAPhen ligands are readily available,especially unsymmetrical ones,which give us a platform to systematically study the substituent effect on f-block elements extraction performance.The performance of unsymmetrical extractants is experimentally confirmed to falls between that of their corresponding symmetrical extractants by extracting UO_(2)^(2+) as the representative f-block element.This work provides a direct and versatile method to synthesize symmetrical and unsymmetrical DAPhen,which paves way for the investigations on their coordination properties with metal ions and other applications.
基金National Natural Science Foundation of China under Grants 62122069,62071431,62072490,62301490Science and Technology Development Fund of Macao,Macao,China under Grant 0158/2022/A+2 种基金Guangdong Basic and Applied Basic Research Foundation(2022A1515011287)MYRG2020-00107-IOTSCFDCT SKL-IOTSC(UM)-2021-2023。
文摘Text semantic extraction has been envisioned as a promising solution to improve the data transmission efficiency with the limited radio resources for the autonomous interactions among machines and things in the future sixth-generation(6G)wireless networks.In this paper,we propose a Chinese text semantic extraction model,namely T-Pointer,to improve the quality of semantic extraction by integrating the Transformer with the pointer-generator network.The proposed T-Pointer model consists of a semantic encoder and a semantic decoder.In the encoding stage,we use the multi-head attention mechanism of the Transformer to extract semantic features from the input Chinese text.In the decoding stage,we first use the Transformer to extract multi-level global text features.Then,we introduce the pointer-generator network model to directly copy the keyword information from the source text.The simulation results demonstrate that the T-Pointer model can improve the bilingual evaluation understudy(BLEU)and recalloriented understudy for gisting evaluation(ROUGE)by 14.69%and 14.87%on average in comparison with the state-of-the-art models,respectively.Also,we implement the T-Pointer model on a semantic communication system based on the universal software radio peripheral(USRP)platform.The result shows that the packet delay of semantic transmission can be reduced by 52.05%on average,compared to traditional information transmission.
基金support from the National Natural Science Foundation of China Regional Innovation and Development Joint Fund(U24A20557)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDC0230403)+3 种基金the National Natural Science Foundation of China(22378393,22208356)“Hundred Talents Program”of the Chinese Academy of Sciencesthe Chinese Academy of Sciences stably supports the youth team plan in the field of basic research(YSBR 038)Key Research&Development projects in Qinghai Province(2023-HZ-805).
文摘This article presents a new synergistic extraction system composed of Cyanex 272(C272,bis(2,4,4-trimethylpentyl)phosphinic acid)and iso-octanol for Sc_(3+) separation.The proposed synergistic system possessed an Sc^(3+) extraction efficiency of 93.5%and a back-extraction efficiency of 82.7%,with selectivity coefficients of β_(Sc/Fe)=459 and β_(Sc/Al)=4241,which are considerably higher as compared to the current extraction systems.The extraction mechanism was studied and interpreted.The enhanced extraction efficiency is attributed to the increased hydrophobicity of the ternary complex,whereas the back-extraction efficiency can be ascribed to the attenuated stability of the complex.C272 and C272–iso-octanol systems also possess considerable surface activity,which is beneficial for the phase separation in solvent extraction.Based on the solvent extraction results,a preliminary study was conducted on polymer inclusion membranes(PIMs)using the binary system for Sc^(3+) separation to avoid the formation of the third phase,achieving an optimal initial flux of PIM of 6.71×10^(−4)mol·m^(−2)·h^(−1).Our results provide valuable information on highly efficient Sc^(3+) separation,and the study on PIM extraction has shown a green alternative to solvent extraction.
基金Dept of Science and Technology,Govt.of India,DST/SEED/SCSP/STI/2019/253.
文摘Chamaedorea seifrizii is a bamboo plant that is mainly used for its air-purifying properties and ornamental value.Due to the scarcity of reports on its phytochemical constitutes,this study was aimed at chemical profiling,phytochemical analysis and evaluation of its in-vitro biological activities of acetone extracts of auxiliary inflorescence and fruits of Chamaedorea seifrizii accompanied by in-silico analysis.Standard techniques were employed for phytochemical screening of phenolics,flavonoids and tannins and anti-oxidant and anti-inflammatory tests.In-silico analysis coupled with molecular dynamics simulation was also conducted to find out interaction of some components to inflammatory responses.Bioactive compounds in auxiliary inflorescence and fruit extracts were studied using a gas chromatography-flame ionization detector(GC-FID).Numerous antioxidant tests were carried out,including those for 2,2-diphenyl-1-picrylhydrazyl(DPPH),hydroxyl radicals,and nitric oxide radicals and shown that all both extracts depicted exorbitant levels of activities with values ranging from 48 to 96%.Results of GC-FID revealed maximum 18-22 constituents in acetone fractions with phenethyl cinnamate and hinokione as predominant components in auxiliary inflorescence and fruits,respectively.In addition,a strong anti-inflammatory activity was observed with acetone containing extracts.In-silico analysis validated the interaction of phytocomponents to inflammation initiation enzymes.Phytochemicals found in Chamaedorea seifrizii extracts may have pharmacological,antioxidant and anti-inflammatory properties.Chamaedorea seifrizii may be used in this study to produce new herbal remedies for a range of illnesses,perhaps resulting in the development of novel drugs.
基金supported by National Natural Science Foundation of China(Grant No.22378066,22108040)Collaboration&Innovation Platform Project of National Independent Innovation Demonstration Zone(Fuzhou,Xiamen&Quanzhou)(Project No:3502ZCQXT2023004).
文摘The extraction of uranium from seawater via membrane adsorption is a promising strategy for ensuring a long-term supply of uranium and the sustainability of nuclear energy.However,this approach has been hindered by the longstanding challenge of identifying sustainable membrane materials.In response,we propose a prototypal hybridization strategy to design a novel series of aminated conjugated microporous polymer(CMPN)@collagen fiber membrane(COLM).These sustainable and low-cost membrane materials allow a rapid and high-affinity kinetic to capture 90%of the uranium in just 30 min from 50 ppm with a high selectivity of Kd>105 mL·g^(−1).They also afford a robustly reusable adsorption capacity as high as 345 mg·g^(−1)that could harvest 1.61 mg·g^(−1)of uranium in a short 7-day real marine engineering in Fujian Province,even though suffered from very low uranium concentration of 3.29μg·L^(−1)and tough influence of salts such as 10.77 g·L^(−1)of Na^(+),1.75μg·L^(−1)of VO_(3)^(−)etc.in the rough seas.The structural evidence from both experimental and theoretical studies confirmed the formation of favorable chelating motifs from the amino group on CMPN-COLM,and the intensification by the synergistic effect from the size-sieving action of CMPN and the capillary inflow effect of COLM.
基金supported by the National Natural Science Foundation of China(No.52122407)the National Key Research&Development Program of China(No.2022YF2906200)the Science and Technology Innovation Program of Hunan Province,China(No.2022RC3048)。
文摘The leaching process and kinetic behavior of lepidolite in hydrochloric acid were explored systematically.The influence of leaching conditions on the leaching efficiency of valuable metals in lepidolite was investigated.Under optimized conditions,the leaching efficiencies of Li,K,Rb,Cs and Al are 92.02%,93.31%,88.59%,86.75%and 81.07%,respectively.Kinetics research results show that the leaching process conforms to the shrinking core model that is under the mixed control of chemical reaction and diffusion through the solid product layer.In addition,the contribution of solid product layer diffusion to the leaching gradually expands as the temperature rises,but it is still significantly less than the contribution of chemical reaction.Cost saving in the neutralizing agent and leaching processes makes hydrochloric acid an economical leaching agent for lepidolite.Finally,the Li2CO3 product with a purity of 99.89%was synthesized from the hydrochloric acid leachate.
文摘Objective:To investigate the effect of a water-soluble nacre extract derived from Pinctada fucata on skeletal muscle aging.Methods:Naturally aged C57BL/6J mice received nacre extract mixed in chow for 12 weeks.Forelimb grip strength,hanging performance,and locomotor activity were assessed.Skeletal muscle remodeling and signaling were evaluated by histology and immunostaining for fibrosis,contractile-marker features,senescence-and DNA damage-associated markers,inflammatory signaling,and mitochondrial proteins.Oxidative status was assessed by determining antioxidant capacity,lipid peroxidation,and oxidative DNA damage.Transcriptomic profiling was also performed,and selected targets were validated by quantitative RT-PCR and immunostaining.In addition,differentiated C2C12 myotubes were exposed to doxorubicin and treated with nacre extract;senescence-associated β-galactosidase,DNA damage signaling,and cell viability were measured.Results:Nacre extract increased forelimb grip strength and showed a positive trend in hanging performance without altering spontaneous locomotion.It also reduced collagen deposition,preserved contractile-marker immunoreactivity,attenuated senescence-and inflammation-associated signals,and increased mitochondrial protein immunoreactivity.Oxidative DNA damage was notably reduced by nacre extract.Transcriptomics indicated modulation of stress/redox programs and increased neurotrophic tyrosine kinase receptor type 2 expression,which were supported by tissue-level validation.In C2C12 myotubes,nacre extract suppressed doxorubicin-induced senescence-associated phenotypes without loss of cell viability.Conclusions:Water-soluble nacre extract mitigates skeletal muscle aging through coordinated modulation of oxidative stress,inflammation,mitochondrial features,and cellular senescence.
基金funded by the Hainan Province Science and Technology Special Fund under Grant ZDYF2024GXJS292.
文摘Deep learning has made significant progress in the field of oriented object detection for remote sensing images.However,existing methods still face challenges when dealing with difficult tasks such as multi-scale targets,complex backgrounds,and small objects in remote sensing.Maintaining model lightweight to address resource constraints in remote sensing scenarios while improving task completion for remote sensing tasks remains a research hotspot.Therefore,we propose an enhanced multi-scale feature extraction lightweight network EM-YOLO based on the YOLOv8s architecture,specifically optimized for the characteristics of large target scale variations,diverse orientations,and numerous small objects in remote sensing images.Our innovations lie in two main aspects:First,a dynamic snake convolution(DSC)is introduced into the backbone network to enhance the model’s feature extraction capability for oriented targets.Second,an innovative focusing-diffusion module is designed in the feature fusion neck to effectively integrate multi-scale feature information.Finally,we introduce Layer-Adaptive Sparsity for magnitude-based Pruning(LASP)method to perform lightweight network pruning to better complete tasks in resource-constrained scenarios.Experimental results on the lightweight platform Orin demonstrate that the proposed method significantly outperforms the original YOLOv8s model in oriented remote sensing object detection tasks,and achieves comparable or superior performance to state-of-the-art methods on three authoritative remote sensing datasets(DOTA v1.0,DOTA v1.5,and HRSC2016).
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Although Named Entity Recognition(NER)in cybersecurity has historically concentrated on threat intelligence,vital security data can be found in a variety of sources,such as open-source intelligence and unprocessed tool outputs.When dealing with technical language,the coexistence of structured and unstructured data poses serious issues for traditional BERT-based techniques.We introduce a three-phase approach for improved NER inmulti-source cybersecurity data that makes use of large language models(LLMs).To ensure thorough entity coverage,our method starts with an identification module that uses dynamic prompting techniques.To lessen hallucinations,the extraction module uses confidence-based self-assessment and cross-checking using regex validation.The tagging module links to knowledge bases for contextual validation and uses SecureBERT in conjunction with conditional random fields to detect entity boundaries precisely.Our framework creates efficient natural language segments by utilizing decoderbased LLMs with 10B parameters.When compared to baseline SecureBERT implementations,evaluation across four cybersecurity data sources shows notable gains,with a 9.4%–25.21%greater recall and a 6.38%–17.3%better F1-score.Our refined model matches larger models and achieves 2.6%–4.9%better F1-score for technical phrase recognition than the state-of-the-art alternatives Claude 3.5 Sonnet,Llama3-8B,and Mixtral-7B.The three-stage architecture identification-extraction-tagging pipeline tackles important cybersecurity NER issues.Through effective architectures,these developments preserve deployability while setting a new standard for entity extraction in challenging security scenarios.The findings show how specific enhancements in hybrid recognition,validation procedures,and prompt engineering raise NER performance above monolithic LLM approaches in cybersecurity applications,especially for technical entity extraction fromheterogeneous sourceswhere conventional techniques fall short.Because of itsmodular nature,the framework can be upgraded at the component level as new methods are developed.
