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
The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recogni...The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.展开更多
In this study,polyacrylic acid(PAA)films were employed as a model system,and a series of PAA films with tunable water wettability was systematically prepared by varying molecular weight and curing temperature.Using at...In this study,polyacrylic acid(PAA)films were employed as a model system,and a series of PAA films with tunable water wettability was systematically prepared by varying molecular weight and curing temperature.Using attenuated total reflectance Fourier-transform infrared spectroscopy(ATR-FTIR),the molecular configurations of surface carboxyl groups(COOH),free carboxyl(COOH_(f))and hydrogen-bonded carboxyl(COOH_(HB),were directly correlated with the polar component of surface energy(γ^(s,p)).By decomposing theγ^(s,p)values of the PAA thin films as a sum of the contributions of COOH_(f)and COOH_(H B),the intrinsic polar component of surface energy of COOH_(H B)(γ_(H B)^(s,p*))was quantified for the first time as 8.34 mN/m,significantly lower than that of COOH_(f)(γ_(f)^(s,p*)=34 mN/m).This result highlights that hydrogen bonding markedly reduces theγ^(s,p),providing a rational explanation for the relatively large water contact angle observed on PAA thin films.Furthermore,it establishes a thermodynamic basis for estimating the fraction of surface COOH_(H B)groups(f H B)from wettability measurements.Further extension of the model to carboxyl-terminated self-assembled monolayers(COOH-SAMs)revealed that surface COOH density(ΣCOOH)critically regulates wetting behavior:whenΣCOOH ranges from 4.30 to 5.25 nm^(-2),COOH groups predominantly exist in a free state and facilitate effective hydration layers,thereby promoting superhydrophilicity.Overall,this study not only establishes a unified thermodynamic framework linking surface COOH configurations to macroscopic wettability,but also validates its universality by extending it to COOH-SAMs systems,thereby providing a unified theoretical framework for the controllable design of hydrophilicity in various COOH-functionalized surfaces.展开更多
Enhanced riverine nitrogen(N)and phosphorus(P)exports from anthropogenic activities have substantially increased primary productivity in downstream waters and induced harmful ecosystem effects.The components of riveri...Enhanced riverine nitrogen(N)and phosphorus(P)exports from anthropogenic activities have substantially increased primary productivity in downstream waters and induced harmful ecosystem effects.The components of riverine nutrient fluxes determine environmental responses that remain largely unknown.We identified different components of riverine N and P exports based on a load-hydrograph analysis of multiple sections of the Yangtze River in China based on long-term daily nutrient fluxes.Our results indicate that the increasing trend of riverine N and P fluxes from upstream to downstream can be reversed by the retention effect of dams and lakes,which is more significant for total phosphorus and its high-flux component than total nitrogen.The greatest nutrient retention along the river was mainly attributed to the Three Gorges Dam,which has a significant retention effect on both N and P fluxes,particularly on the high flux and TP.While high nutrient fluxes dominate upstream,middle and low fluxes dominate downstream.Significant but uncommon trends were observed for all nutrient flux components along the river.While both,medium and low flux percentages increase significantly,those of high flux decrease.The net change of N and P fluxes along the Yangtze River do not coincide in space,indicating heterogeneity between the river’s source and sink of N and P.Knowledge of the inconsistent alteration of riverine nutrient flux and its components should facilitate efforts to make better measures to mitigate nutrient-related problems in the Yangtze River.展开更多
With the legislative development,the organic and inorganic composition separation has become the primary requirement for sewer sediment disposal,however the relevant technology has been rarely reported and the driving...With the legislative development,the organic and inorganic composition separation has become the primary requirement for sewer sediment disposal,however the relevant technology has been rarely reported and the driving mechanism was still unclear.In this study,direct disintegration of biopolymers and indirect broken of connection point were investigated on the hydrolysis and component separation.Three typical sewer sediment treatment approaches,i.e.,alkaline,thermal and cation exchange treatments were proposed,which represented the hydrolysis-driving forces of chemical hydrolysis,physical hydrolysis and innovative cation bridging break-age.The results showed that the organic and inorganic separation rates of sewer sediment driven by alkaline,thermal and cation exchange treatments reached 21.26%,23.80%,and 19.56%-48.0%,respectively,compared to 4.43%in control.The secondary structure of proteins was disrupted,transitioning from𝛼α-helix to𝛽β-turn and random coil.Meanwhile,much biopolymers were released from solid to the liquid phase.From thermody-namic perspective,sewer sediment deposition was controlled by short-range interfacial interactions described by extended Derjaguin-Landau-Verwey-Overbeek theory.Additionally,the separation of organic and inorganic components was positively correlated with the thermodynamic parameters(Corr=0.87),highlighted the robust-ness of various driving forces.And the flocculation energy barriers were 2.40(alkaline),1.60 times(thermal),and 4.02–4.97 times(cation exchange)compared to control group.The findings revealed the contrition differ-ence of direct disintegration of gelatinous biopolymers and indirect breakage of composition connection sites in sediment composition separation,filling the critical gaps in understanding the specific mechanisms of sediment biopolymer disintegration and intermolecular connection breakage.展开更多
Enhancing the resilience of critical infrastructure(CI)systems has become a focal point of national and inter-national policies.However,the formulation of resilience enhancement strategies often requires component-(i....Enhancing the resilience of critical infrastructure(CI)systems has become a focal point of national and inter-national policies.However,the formulation of resilience enhancement strategies often requires component-(i.e.asset-)level prioritization,which entails many complexities.Acknowledging the complex and interdependent nature of infrastructure systems,this paper aims to aid researchers,practitioners and policy-makers by pre-senting a review of the relative literature and current state-of-the-art,and by identifying future research op-portunities to improve the applicability and operationalizability of CI component identification and prioritization methods.Theoretical and practical applications are reviewed for definitions,analysis and modelling approaches regarding the resilience of interdependent infrastructure systems.A detailed review of infrastructure criticality definitions,component criticality assessment and prioritization frameworks,from scientific,policy and other documents,is presented.A discussion on social justice and equity dimensions therein is included,which have the potential to greatly influence decisions and should always be incorporated in infrastructure planning and in-vestment discussions.The findings of this review are discussed in terms of applicability and operationalizability.Key recommendations for future research include:(i)developing quantification frameworks for CI component criticality based on formal definitions and multiple criteria,(ii)incorporating the entire resilience cycle of CI in component prioritization,(iii)accounting for the socio-technical nature of CI systems by integrating social di-mensions and their wider operating environment and(iv)developing comprehensive model validation,cali-bration and uncertainty analysis frameworks.展开更多
In this study,a polymer acceptor named BT-Cl with a“bridging”structure,which contained a benzodithiophene unit analogous to that of donor D18,and cyano(CN)groups and heterocyclic structures similar to those in accep...In this study,a polymer acceptor named BT-Cl with a“bridging”structure,which contained a benzodithiophene unit analogous to that of donor D18,and cyano(CN)groups and heterocyclic structures similar to those in acceptor N3,was synthesized.The“bridging”structure ensured good compatibility of BT-Cl with both D18 and N3,and effectively helped to reduce the large phase separation size of D18/N3 binary blend film when added as a third component.Meanwhile,the addition of BT-Cl to the D18/N3 blend can improve the crystallinity and enhance the light absorption efficiency to some extent.The“bridging”structure also resulted higher lowest unoccupied molecular orbital(LUMO)energy level of BT-Cl than that of N3,which effectively improve the open-circuit voltage(VOC)of the ternary device and consequently the power conversion efficiency(PCE).This work showed that the polymer with“bridging”structure as the third component was an effective strategy to decrease the large phase separation size.展开更多
The multi-pass intermittent local loading process,which features a more flexible processing path,can further enhance the second material distribution during local loading,improve the formability of components,and redu...The multi-pass intermittent local loading process,which features a more flexible processing path,can further enhance the second material distribution during local loading,improve the formability of components,and reduce forming loads.However,the absence of compatible forming equipment makes it difficult to control the constraint in the unloaded zones during the forming process.This difficulty complicates coordination and control of deformation,particularly for asymmetric rib-web components.Additionally,the current implementation involves multi-fire heating,a long process flow,and high energy consumption,which limits the popularization and application of the local loading process.In this study,a new multi-pass local loading hydraulic forming apparatus that can quickly and reliably switch between heavy-load deformation and low-load constraint for different local loading sub-dies was developed.A 10-tonne laboratory prototype was developed,and the forming characteristics during the forming process as well as the response characteristics of the hydraulic system during the multi-pass intermittent local loading of rib-web component were investigated using numerical simulations and physical experiments.Results indicated that,compared to a whole loading process with the same initial geometry of billet,the total forming load(i.e.,the sum of loaded and restrained loads)is reduced by more than 40%with the local loading process,and by nearly 50%with multi-pass local loading.The multi-pass local loading process allows for more effective control of material flow compared to single-pass local loading,leading to improved cavity filling and reduced flow line disturbance.For a large-scale,complex titanium alloy bulkhead,the cavity filling problem was addressed by optimizing the multi-pass local loading path with an unequal thickness billet.The dynamic performance of the multi-pass local loading hydraulic system was found to be robust,with stable pressure transitions during motion and load switching for the sub-die(s).The dynamic characteristic of the hydraulic cylinder when switching from non-moving/unloaded state to a moving/loading state are consistent whether a load is present or not.However,the dynamic characteristics differ when switching from a moving/loading state to non-moving/unloaded state,showing opposite behavior.The developed hydraulic drive mechanism provides a way for implementation of multi-pass local loading without auxiliary operation and extra heating.The results of the study provide a foundation for the industrial production of large-scale,complex components with reduced force requirement and low-energy consumption.展开更多
Accurate assessment of seismic landslide susceptibility is crucial for disaster prevention and emergency decision-making.Although machine learning methods have been widely applied in this field,they exhibit a strong d...Accurate assessment of seismic landslide susceptibility is crucial for disaster prevention and emergency decision-making.Although machine learning methods have been widely applied in this field,they exhibit a strong dependence on large quantities of highquality samples,resulting in significantly low prediction accuracy of existing studies under data-scarce or crossregional prediction scenarios,which fail to meet practical application requirements.To address this issue,this study proposes an intelligent prediction model integrating transfer learning and a sampling optimization strategy,aiming to enhance the accuracy and applicability of seismic landslide susceptibility assessment.The model first improves the sample collection method through the sampling optimization strategy to enhance the precision and representativeness of training samples.This not only ensures the accuracy of origin area training but also further strengthens the model's predictive ability in the target area.Subsequently,it incorporates Transfer Component Analysis(TCA)to overcome the differences in environmental characteristics between the origin area and target area,and couples TCA with the Light GBM algorithm to construct the TCA-Light GBM model,realizing the assessment of seismic landslide susceptibility in sample-free areas.Validated through case studies of the Jiuzhaigou and Luding earthquakes,the results demonstrate that the proposed TCALight GBM transfer learning method exhibits excellent applicability in seismic landslide susceptibility prediction.After optimization with the TCA algorithm,the model's prediction performance in the target domain is significantly improved,with the AUC value increasing from 0.719 to 0.827,representing an increase of approximately 15.02%.This indicates that TCA technology can effectively alleviate the feature distribution discrepancy between the source domain and target domain,enhancing the model's generalization ability.The method is particularly suitable for scenarios with data scarcity and cross-regional prediction and can provide reliable technical support for the emergency response and risk prevention and control of seismic hazards.展开更多
The Toraja Highlands,encompassing Tana Toraja and North Toraja,form the strategic upper reaches of the Saddang Watershed in South Sulawesi,where steep terrain,active land-cover change,and high ecological sensitivity c...The Toraja Highlands,encompassing Tana Toraja and North Toraja,form the strategic upper reaches of the Saddang Watershed in South Sulawesi,where steep terrain,active land-cover change,and high ecological sensitivity converge.This study addresses the need for an objective and validated ecological sensitivity map to support sustainable mountain watershed management.We construct an ecological sensitivity index based on principal component analysis using four key indicators:land cover,vegetation density(NDVI),slope,and rainfall,and evaluate its reliability through multi-source validation.Inputs integrate national elevation models,Landsat 8 imagery,and satellite-derived rainfall.Rainfall represents a multi-year climatology for 2015–2024,whereas land cover and NDVI reflect recent surface conditions derived from a cloud-free 2024 composite.The resulting sensitivity zonation indicates that 41.10%of Tana Toraja and 67.11%of North Toraja fall into the very high sensitivity class,concentrated on steep slopes and intensively converted landscapes.Eventbased spatial cross-validation against independent landslide records yields overall accuracies of 67.65%and 66.67%,while field verification produces Kappa values of 0.847 and 0.871.Stakeholder appraisal further corroborates the mapped patterns.Together,these convergent lines of evidence identify priority areas for reforestation,soil conservation,slope stabilization,and sustainable watershed management.The transparent and reproducible workflow supports evidence-based risk reduction and resilience building in the upper reaches of the Saddang Watershed.展开更多
[Objectives]To develop an HPLC fingerprint analysis method for the medicinal material of Lysimachia foenum-graecum Hance,thereby providing a foundation for its quality control.[Methods]Samples of L.foenum-graecum coll...[Objectives]To develop an HPLC fingerprint analysis method for the medicinal material of Lysimachia foenum-graecum Hance,thereby providing a foundation for its quality control.[Methods]Samples of L.foenum-graecum collected from 10 distinct locations in Guangxi were analyzed using HPLC,and chromatographic fingerprints were established.The Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine(2012 Edition)was employed for common peak calibration and similarity evaluation.Additionally,principal component analysis was performed on the common peak area data.[Results]An HPLC fingerprint of L.foenum-graecum was developed,identifying a total of 13 common peaks.Among these,four characteristic components were specifically identified:chlorogenic acid,myricetin,quercetin,and kaempferol.The kaempferol chromatographic peak,exhibiting good resolution and a stable peak shape,was selected as the reference peak.The similarity indices between the fingerprints of the 10 sample batches and the reference fingerprint ranged from 0.954 to 0.995,indicating a relatively high consistency in the chemical composition of L.foenum-graecum from different origins.Principal component analysis identified two principal components,which together accounted for 89.45%of the cumulative variance,effectively capturing the primary chemical differences among the samples.[Conclusions]The established HPLC fingerprint method is straightforward to implement,stable,reliable,and exhibits high specificity.When combined with similarity evaluation and principal component analysis,it offers a scientific basis for developing quality standards for L.foenum-graecum medicinal materials.展开更多
Analyzing the driving behavior of autonomous vehicles(AV)in mixed traffic conditions at urban intersections has become increasingly important for improving intersection design,providing infrastructure-based guidance i...Analyzing the driving behavior of autonomous vehicles(AV)in mixed traffic conditions at urban intersections has become increasingly important for improving intersection design,providing infrastructure-based guidance information,and developing capability-enhanced AV perception systems.This study investigated the contributing factors affecting AV driving behavior using theWaymo Open Dataset.Binarized autonomous driving stability metrics,derived via a kernel density estimation,served as the target variables for a random forest classification model.The model’s input variables included 15 factors divided into four types:intersection-related,surrounding object-related,road infrastructure-related,and time-of-day-related types.The random forest classification model was employed to identify the key factors affecting autonomous driving behavior.In addition,the identified factors were further ranked based on feature importance.SHAP analysis was utilized to enhance model interpretability by quantifying the contribution of each factor and identifying their directional impacts.The type of intersection factor was found to have an importance of 0.243 and was the most influential factor on autonomous driving behavior.On average,intersection-related factors had an importance of 0.196,which is approximately a 31.1%margin over the average importance of surrounding object-related factors.Additionally,the surrounding object-related factors that were collected through sensors on the autonomous vehicle had a high degree of feature importance,especially with the number of pedestrians having the highest importance(0.107)of the types of objects.The correlation between these findings can contribute to the development of various treatments to improvemore harmonized AVs’maneuvering with other road users and facilities in urban mixed traffic environments.展开更多
[Objectives]This study was conducted to isolate and identify the components from stems of Polyalthia plagioneura.[Methods]The compounds were isolated and purified by silica gel column,Sephadex LH-20,and C_(18) chromat...[Objectives]This study was conducted to isolate and identify the components from stems of Polyalthia plagioneura.[Methods]The compounds were isolated and purified by silica gel column,Sephadex LH-20,and C_(18) chromatography.Their chemical structures were elucidated on the basis of physicochemical properties and spectral data.[Results]Five compounds were isolated and identified as:di(2-ethylhexyl)phthalate(1),cinnamic anhydride(2),phthalic acid(3),citric acid(4),and syringaldehyde(5).[Conclusions]All compounds were isolated from this plant for the first time.展开更多
Predictive maintenance(PdM)is vital for ensuring the reliability,safety,and cost efficiency of heavyduty vehicle fleets.However,real-world sensor data are often highly imbalanced,noisy,and temporally irregular,posing ...Predictive maintenance(PdM)is vital for ensuring the reliability,safety,and cost efficiency of heavyduty vehicle fleets.However,real-world sensor data are often highly imbalanced,noisy,and temporally irregular,posing significant challenges to model robustness and deployment.Using multivariate time-series data from Scania trucks,this study proposes a novel PdM framework that integrates efficient feature summarization with cost-sensitive hierarchical classification.First,the proposed last_k_summary method transforms recent operational records into compact statistical and trend-based descriptors while preserving missingness,allowing LightGBM to leverage its inherent split rules without ad-hoc imputation.Then,a two-stage LightGBM framework is developed for fault detection and severity classification:Stage A performs safety-prioritized fault screening(normal vs.fault)with a false-negativeweighted objective,and Stage B refines the detected faults into four severity levels through a cascaded hierarchy of binary classifiers.Under the official cost matrix of the IDA Industrial Challenge,the framework achieves total misclassification costs of 36,113(validation)and 36,314(test),outperforming XGBoost and Bi-LSTM by 3.8%-13.5%while maintaining high recall for the safety-critical class(0.83 validation,0.77 test).These results demonstrate that the proposed approach not only improves predictive accuracy but also provides a practical and deployable PdM solution that reduces maintenance cost,enhances fleet safety,and supports data-driven decision-making in industrial environments.展开更多
Ulva lactuca whole components served as a carbon source for high-density fermentation of Bifidobacterium,yielding a low-cost,highly biocompatible Ulva lactuca bifidobacterium ferment filtrate(ULBFF).Its peptide profil...Ulva lactuca whole components served as a carbon source for high-density fermentation of Bifidobacterium,yielding a low-cost,highly biocompatible Ulva lactuca bifidobacterium ferment filtrate(ULBFF).Its peptide profile and molecular weight distribution were characterized by LC/MS.Cosmetic potential was systematically evaluated through stability testing,HET-CAM test,ABTS+∙/DPPH∙scavenging,NO inhibition,melanin suppression,and type Ⅰ collagen promotion.The results indicated a rich distribution of peptides,predominantly low-molecular-weight oligopeptides,with 92.92%of peptides containing≤20 amino acids and 84.89%of components having a molecular weight<500 Da.Formulations exhibited excellent stability and low irritation.Furthermore,they showed significantly enhanced efficacy in key areas,including antioxidant and antiinflammatory activity,melanin suppression,and collagen promotion.The ULBFF improved multifunctional performance while maintaining formulation stability and safety,demonstrating high scalability and potential for marine bioresource utilization in functional cosmetics.展开更多
Lignocellulosic biomass is the most abundant re-newable resource on Earth,boasting advan-tages such as wide avail-ability and negative car-bon emissions.Especial-ly,efficient separation of lignocellulose into cellu-lo...Lignocellulosic biomass is the most abundant re-newable resource on Earth,boasting advan-tages such as wide avail-ability and negative car-bon emissions.Especial-ly,efficient separation of lignocellulose into cellu-lose,hemicellulose and lignin,and realizing val-orization of these compo-nents are more responsive to the development needs of biomass refinery and the green chem-istry era.This review outlines the main components of lignocellulose and briefly summerizes their utilization in chemical raw materials and energy production.It mainly focused on cur-rent advances in component separation methods of lignocellulose by organic solvents,ionic liquids and deep eutectic solvents.The design of separation methods,understanding of sepa-ration mechanisms,and optimization of reaction systems in each method are highlighted in detail.Furthermore,the ongoing challenges and future directions based on mechanism and in-dustrialization are critically discussed.Our goal is to elucidate the separation mechanisms and principles of method design,providing guidance for the development of highly efficient com-ponent separation methods of lignocellulose.展开更多
Crassostrea gigas has good taste and high nutritional value;however,there are few assessments of comprehensive and panoramic analyses of the nutritional quality of the northern oyster.To study the nutritional characte...Crassostrea gigas has good taste and high nutritional value;however,there are few assessments of comprehensive and panoramic analyses of the nutritional quality of the northern oyster.To study the nutritional characteristics of C.gigas from different sources(ploidy,region,size,and culture mode),C.gigas from various ploidy(diploid and triploid),regions(Rushan,Off-site fattening,and Rongcheng),sizes(small,medium,and large)and culture modes(nearshore and offshore)were selected for comparative analyses.The nutritional components(moisture,protein,fat,and mineral),flavor substances(taste amino acids,nucleotides,and succinic acid),and functional indices(eicosapentaenoic acid(EPA),docosahexaenoic acid(DHA),and taurine)of C.gigas were determined.Principal component analysis(PCA)was used to comprehensively evaluate the oysters and investigate the variations in nutritional quality.The PCA results indicate that protein,essential fatty acids,selenium,zinc,taste amino acids,taurine,EPA,and DHA were core components contributing to 82.25%of the cumulative variance,providing a more comprehensive reflection of the nutrient composition of C.gigas.The extensive quality rankings for the C.gigas were as follows:diploid>triploid,Rushan>fattening>Rongcheng,medium>large>small,and offshore>nearshore.The score rank revealed that diploid oysters of medium-size from Rushan demonstrated superior nutritional quality compared to other tested samples.This is the first comprehensive and systematic investigation of C.gigas in northern China to reveal the feature of nutrients,flavor,and functional components.The study provided data support for the culture,consumption,processing,research,and nutritional quality improvement of oyster industry.展开更多
The physicochemical properties of SUS304 foil surfaces are crucial to their applications.Pulsed laser modification was applied to 30μm thick SUS304 foils to systematically investigate the influence of laser energy on...The physicochemical properties of SUS304 foil surfaces are crucial to their applications.Pulsed laser modification was applied to 30μm thick SUS304 foils to systematically investigate the influence of laser energy on surface characteristics.Through multidimensional characterization of surface morphology,three-dimensional profiles and roughness,contact angle,and chemical composition,the structure-function correlation between laser energy and the physicochemical properties of steel surface was revealed.With increasing laser energy,the surface morphology of the steel transitions from a directional rolling-marked structure to a uniform sponge-like isotropic structure,accompanied by increased peak density and an expanded interfacial area.Additionally,the chemical state on the metal surface gradually stabilizes from unstable redox reactions,forming a stable oxide layer and significantly increasing active hydroxyl groups,thereby effectively improving surface wettability.Single lap shear tests reveal an enhancement in the bonding strength of steel/carbon fiber reinforced composites joints after laser modification,which is attributed to the synergistic effects of mechanical interlocking,enhanced wettability,and chemical bonding at the interface.The demonstrated potential of laser surface treatment for modifying SUS304 ultra-thin foils provides theoretical support and technical reference for its application in fiber metal laminates.展开更多
Accurate assessment of site quality in coastal Casuarina equisetifolia(C.equisetifolia)plantations is essential for enhancing the protective function of shelterbelts and implementing site-specific afforestation strate...Accurate assessment of site quality in coastal Casuarina equisetifolia(C.equisetifolia)plantations is essential for enhancing the protective function of shelterbelts and implementing site-specific afforestation strategies.However,traditional ground-based surveys are limited in spatial coverage and efficiency,hindering effective forest management.To overcome these limitations,this study developed an integrated assessment framework that couples ground-based modeling with remote sensing inversion to achieve large-scale site quality mapping.Field investigations on Pingtan Island,Fujian Province,China,were used to establish a ground-based evaluation model.Soil fertility was quantified using Principal Component Analysis(PCA),and principal components were classified into discrete fertility grades through K-means clustering.These grades,together with topographic variables,were incorporated into a site quality classification model constructed using Quantification Theory I.The point-based model was subsequently extrapolated using Landsat 9 imagery to generate a spatially continuous site quality map.Spatial autocorrelation(Moran’s Ⅰ)and LISA clustering were further employed to interpret spatial patterns.Results indicate that coastal sandy soils in the study area are generally nutrient-poor,with tree growth primarily constrained by total nitrogen,organic matter,available phosphorus,and total phosphorus.The five most influential site factors,ranked by importance,are soil fertility,distance from the coastline,aspect,slope gradient,and elevation.Optimal conditions for C.equisetifolia growth include fertile soil,location>1000 m from the coastline,south-facing or semi-sunny slopes,slope gradients<15°,and elevations between 10-100 m.Only 11.94%of the area was classified as high-quality(Grade I),while 61.74%fell into moderate or poor grades(Grades Ⅲ and Ⅳ),indicating that most plantations are located on suboptimal sites.This study provides scientific support for improving the precision and sustainability of coastal shelterbelt planning and management,offering practical insights for afforestation strategies,forest restoration,and ecological forestry development in coastal zones.展开更多
Objective:Triple-negative breast cancer(TNBC)is highly aggressive and lacks an effective targeted therapy.This study aimed to elucidate the functions and possible mechanisms of action of zinc finger miz-type containin...Objective:Triple-negative breast cancer(TNBC)is highly aggressive and lacks an effective targeted therapy.This study aimed to elucidate the functions and possible mechanisms of action of zinc finger miz-type containing 2(ZMIZ2)and minichromosome maintenance complex component 3(MCM3)in TNBC progression.Methods:The relationship between ZMIZ2 expression and clinical characteristics of TNBC was investigated.In vitro and in vivo experiments were performed to investigate the role of ZMIZ2 dysregulation in TNBC cell malignant behaviors.The regulatory relationship between ZMIZ2 and MCM3 was also explored.Transcriptome sequencing was performed to elucidate possible mechanisms underlying the ZMIZ2/MCM3 axis in TNBC.Results:High ZMIZ2 expression levels were associated with the malignant degree of TNBC.ZMIZ2 overexpression promoted TNBC cell proliferation,migration,and invasion;inhibited apoptosis;and induced G1 phase cell cycle arrest,whereas knockdown of ZMIZ2 had the opposite effect.ZMIZ2 directly targeted and positively regulated MCM3 expression.MCM3 knockdown reversed the effect of ZMIZ2 overexpression on TNBC tumor growth both in vitro and in vivo.High MCM3 expression levels were linked to the degree of malignancy and poor prognosis in TNBC.The differentially expressed genes associated with the ZMIZ2/MCM3 axis were significantly enriched in multiple pathways,such as the mitogen-activated protein kinase(MAPK),mechanistic target of rapamycin(mTOR),Wnt,and Ras signaling pathways,as verified by The Cancer Genome Atlas data.Conclusions:ZMIZ2 and MCM3 were highly expressed in TNBC.ZMIZ2 promoted the development by positively regulating MCM3 expression.Key pathways,such as the Ras/MAPK,phosphatidylinositol 3-kinase(PI3K)/protein kinase B(AKT)/mTOR,and Wnt signaling pathways,may be key downstreammechanisms.展开更多
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The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.
文摘In this study,polyacrylic acid(PAA)films were employed as a model system,and a series of PAA films with tunable water wettability was systematically prepared by varying molecular weight and curing temperature.Using attenuated total reflectance Fourier-transform infrared spectroscopy(ATR-FTIR),the molecular configurations of surface carboxyl groups(COOH),free carboxyl(COOH_(f))and hydrogen-bonded carboxyl(COOH_(HB),were directly correlated with the polar component of surface energy(γ^(s,p)).By decomposing theγ^(s,p)values of the PAA thin films as a sum of the contributions of COOH_(f)and COOH_(H B),the intrinsic polar component of surface energy of COOH_(H B)(γ_(H B)^(s,p*))was quantified for the first time as 8.34 mN/m,significantly lower than that of COOH_(f)(γ_(f)^(s,p*)=34 mN/m).This result highlights that hydrogen bonding markedly reduces theγ^(s,p),providing a rational explanation for the relatively large water contact angle observed on PAA thin films.Furthermore,it establishes a thermodynamic basis for estimating the fraction of surface COOH_(H B)groups(f H B)from wettability measurements.Further extension of the model to carboxyl-terminated self-assembled monolayers(COOH-SAMs)revealed that surface COOH density(ΣCOOH)critically regulates wetting behavior:whenΣCOOH ranges from 4.30 to 5.25 nm^(-2),COOH groups predominantly exist in a free state and facilitate effective hydration layers,thereby promoting superhydrophilicity.Overall,this study not only establishes a unified thermodynamic framework linking surface COOH configurations to macroscopic wettability,but also validates its universality by extending it to COOH-SAMs systems,thereby providing a unified theoretical framework for the controllable design of hydrophilicity in various COOH-functionalized surfaces.
基金supported by the National Key Research and Development Program of China(No.2021YFC3201004)the Program for Guangdong Introducing Innovative and Entrepreneurial Teams(No.2021ZT090543).
文摘Enhanced riverine nitrogen(N)and phosphorus(P)exports from anthropogenic activities have substantially increased primary productivity in downstream waters and induced harmful ecosystem effects.The components of riverine nutrient fluxes determine environmental responses that remain largely unknown.We identified different components of riverine N and P exports based on a load-hydrograph analysis of multiple sections of the Yangtze River in China based on long-term daily nutrient fluxes.Our results indicate that the increasing trend of riverine N and P fluxes from upstream to downstream can be reversed by the retention effect of dams and lakes,which is more significant for total phosphorus and its high-flux component than total nitrogen.The greatest nutrient retention along the river was mainly attributed to the Three Gorges Dam,which has a significant retention effect on both N and P fluxes,particularly on the high flux and TP.While high nutrient fluxes dominate upstream,middle and low fluxes dominate downstream.Significant but uncommon trends were observed for all nutrient flux components along the river.While both,medium and low flux percentages increase significantly,those of high flux decrease.The net change of N and P fluxes along the Yangtze River do not coincide in space,indicating heterogeneity between the river’s source and sink of N and P.Knowledge of the inconsistent alteration of riverine nutrient flux and its components should facilitate efforts to make better measures to mitigate nutrient-related problems in the Yangtze River.
基金supported by Shaanxi Key Research and Development Program(No.2024SF-YBXM-546)the National Natural Science Foundation of China(No.52470161)the State Key Laboratory of Pollution Control and Resource Reuse Foundation(No.PCRRF21007).
文摘With the legislative development,the organic and inorganic composition separation has become the primary requirement for sewer sediment disposal,however the relevant technology has been rarely reported and the driving mechanism was still unclear.In this study,direct disintegration of biopolymers and indirect broken of connection point were investigated on the hydrolysis and component separation.Three typical sewer sediment treatment approaches,i.e.,alkaline,thermal and cation exchange treatments were proposed,which represented the hydrolysis-driving forces of chemical hydrolysis,physical hydrolysis and innovative cation bridging break-age.The results showed that the organic and inorganic separation rates of sewer sediment driven by alkaline,thermal and cation exchange treatments reached 21.26%,23.80%,and 19.56%-48.0%,respectively,compared to 4.43%in control.The secondary structure of proteins was disrupted,transitioning from𝛼α-helix to𝛽β-turn and random coil.Meanwhile,much biopolymers were released from solid to the liquid phase.From thermody-namic perspective,sewer sediment deposition was controlled by short-range interfacial interactions described by extended Derjaguin-Landau-Verwey-Overbeek theory.Additionally,the separation of organic and inorganic components was positively correlated with the thermodynamic parameters(Corr=0.87),highlighted the robust-ness of various driving forces.And the flocculation energy barriers were 2.40(alkaline),1.60 times(thermal),and 4.02–4.97 times(cation exchange)compared to control group.The findings revealed the contrition differ-ence of direct disintegration of gelatinous biopolymers and indirect breakage of composition connection sites in sediment composition separation,filling the critical gaps in understanding the specific mechanisms of sediment biopolymer disintegration and intermolecular connection breakage.
基金supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement No.101037424.
文摘Enhancing the resilience of critical infrastructure(CI)systems has become a focal point of national and inter-national policies.However,the formulation of resilience enhancement strategies often requires component-(i.e.asset-)level prioritization,which entails many complexities.Acknowledging the complex and interdependent nature of infrastructure systems,this paper aims to aid researchers,practitioners and policy-makers by pre-senting a review of the relative literature and current state-of-the-art,and by identifying future research op-portunities to improve the applicability and operationalizability of CI component identification and prioritization methods.Theoretical and practical applications are reviewed for definitions,analysis and modelling approaches regarding the resilience of interdependent infrastructure systems.A detailed review of infrastructure criticality definitions,component criticality assessment and prioritization frameworks,from scientific,policy and other documents,is presented.A discussion on social justice and equity dimensions therein is included,which have the potential to greatly influence decisions and should always be incorporated in infrastructure planning and in-vestment discussions.The findings of this review are discussed in terms of applicability and operationalizability.Key recommendations for future research include:(i)developing quantification frameworks for CI component criticality based on formal definitions and multiple criteria,(ii)incorporating the entire resilience cycle of CI in component prioritization,(iii)accounting for the socio-technical nature of CI systems by integrating social di-mensions and their wider operating environment and(iv)developing comprehensive model validation,cali-bration and uncertainty analysis frameworks.
基金financially supported by the National Natural Science Foundation of China(No.52203024)the Natural Science Foundation of Shandong Province(No.ZR2022QE135)+3 种基金the Youth Innovation Team Project of Shandong Provincial University(No.2023KJ330)the Major Scientific Research Project for the Construction of State Key Lab(No.2025ZDGZ02)the Doctoral Research Foundation of SWUST(No.22zx7129)the Natural Science Foundation of Sichuan Province of China(No.2024NSFSC2006).
文摘In this study,a polymer acceptor named BT-Cl with a“bridging”structure,which contained a benzodithiophene unit analogous to that of donor D18,and cyano(CN)groups and heterocyclic structures similar to those in acceptor N3,was synthesized.The“bridging”structure ensured good compatibility of BT-Cl with both D18 and N3,and effectively helped to reduce the large phase separation size of D18/N3 binary blend film when added as a third component.Meanwhile,the addition of BT-Cl to the D18/N3 blend can improve the crystallinity and enhance the light absorption efficiency to some extent.The“bridging”structure also resulted higher lowest unoccupied molecular orbital(LUMO)energy level of BT-Cl than that of N3,which effectively improve the open-circuit voltage(VOC)of the ternary device and consequently the power conversion efficiency(PCE).This work showed that the polymer with“bridging”structure as the third component was an effective strategy to decrease the large phase separation size.
基金the supports of the National Natural Science Foundation of China(Grant No.52375378)。
文摘The multi-pass intermittent local loading process,which features a more flexible processing path,can further enhance the second material distribution during local loading,improve the formability of components,and reduce forming loads.However,the absence of compatible forming equipment makes it difficult to control the constraint in the unloaded zones during the forming process.This difficulty complicates coordination and control of deformation,particularly for asymmetric rib-web components.Additionally,the current implementation involves multi-fire heating,a long process flow,and high energy consumption,which limits the popularization and application of the local loading process.In this study,a new multi-pass local loading hydraulic forming apparatus that can quickly and reliably switch between heavy-load deformation and low-load constraint for different local loading sub-dies was developed.A 10-tonne laboratory prototype was developed,and the forming characteristics during the forming process as well as the response characteristics of the hydraulic system during the multi-pass intermittent local loading of rib-web component were investigated using numerical simulations and physical experiments.Results indicated that,compared to a whole loading process with the same initial geometry of billet,the total forming load(i.e.,the sum of loaded and restrained loads)is reduced by more than 40%with the local loading process,and by nearly 50%with multi-pass local loading.The multi-pass local loading process allows for more effective control of material flow compared to single-pass local loading,leading to improved cavity filling and reduced flow line disturbance.For a large-scale,complex titanium alloy bulkhead,the cavity filling problem was addressed by optimizing the multi-pass local loading path with an unequal thickness billet.The dynamic performance of the multi-pass local loading hydraulic system was found to be robust,with stable pressure transitions during motion and load switching for the sub-die(s).The dynamic characteristic of the hydraulic cylinder when switching from non-moving/unloaded state to a moving/loading state are consistent whether a load is present or not.However,the dynamic characteristics differ when switching from a moving/loading state to non-moving/unloaded state,showing opposite behavior.The developed hydraulic drive mechanism provides a way for implementation of multi-pass local loading without auxiliary operation and extra heating.The results of the study provide a foundation for the industrial production of large-scale,complex components with reduced force requirement and low-energy consumption.
文摘Accurate assessment of seismic landslide susceptibility is crucial for disaster prevention and emergency decision-making.Although machine learning methods have been widely applied in this field,they exhibit a strong dependence on large quantities of highquality samples,resulting in significantly low prediction accuracy of existing studies under data-scarce or crossregional prediction scenarios,which fail to meet practical application requirements.To address this issue,this study proposes an intelligent prediction model integrating transfer learning and a sampling optimization strategy,aiming to enhance the accuracy and applicability of seismic landslide susceptibility assessment.The model first improves the sample collection method through the sampling optimization strategy to enhance the precision and representativeness of training samples.This not only ensures the accuracy of origin area training but also further strengthens the model's predictive ability in the target area.Subsequently,it incorporates Transfer Component Analysis(TCA)to overcome the differences in environmental characteristics between the origin area and target area,and couples TCA with the Light GBM algorithm to construct the TCA-Light GBM model,realizing the assessment of seismic landslide susceptibility in sample-free areas.Validated through case studies of the Jiuzhaigou and Luding earthquakes,the results demonstrate that the proposed TCALight GBM transfer learning method exhibits excellent applicability in seismic landslide susceptibility prediction.After optimization with the TCA algorithm,the model's prediction performance in the target domain is significantly improved,with the AUC value increasing from 0.719 to 0.827,representing an increase of approximately 15.02%.This indicates that TCA technology can effectively alleviate the feature distribution discrepancy between the source domain and target domain,enhancing the model's generalization ability.The method is particularly suitable for scenarios with data scarcity and cross-regional prediction and can provide reliable technical support for the emergency response and risk prevention and control of seismic hazards.
基金funded by the Ministry of Higher Education,Science and Technology,Republic of Indonesia through the Indonesia Collaborative Research(Riset Kolaborasi Indonesia)grant(Number:01319/UN4.22/PT.01.03/2025)。
文摘The Toraja Highlands,encompassing Tana Toraja and North Toraja,form the strategic upper reaches of the Saddang Watershed in South Sulawesi,where steep terrain,active land-cover change,and high ecological sensitivity converge.This study addresses the need for an objective and validated ecological sensitivity map to support sustainable mountain watershed management.We construct an ecological sensitivity index based on principal component analysis using four key indicators:land cover,vegetation density(NDVI),slope,and rainfall,and evaluate its reliability through multi-source validation.Inputs integrate national elevation models,Landsat 8 imagery,and satellite-derived rainfall.Rainfall represents a multi-year climatology for 2015–2024,whereas land cover and NDVI reflect recent surface conditions derived from a cloud-free 2024 composite.The resulting sensitivity zonation indicates that 41.10%of Tana Toraja and 67.11%of North Toraja fall into the very high sensitivity class,concentrated on steep slopes and intensively converted landscapes.Eventbased spatial cross-validation against independent landslide records yields overall accuracies of 67.65%and 66.67%,while field verification produces Kappa values of 0.847 and 0.871.Stakeholder appraisal further corroborates the mapped patterns.Together,these convergent lines of evidence identify priority areas for reforestation,soil conservation,slope stabilization,and sustainable watershed management.The transparent and reproducible workflow supports evidence-based risk reduction and resilience building in the upper reaches of the Saddang Watershed.
基金Supported by 2023 Self-funded Research Project of the Guangxi Zhuang Autonomous Region Administration of Traditional Chinese Medicine(GXZYL20230369)2022 Internal Talent Research Project of Affiliated Hospital of Youjiang Medical University for Nationalities(Y202210319).
文摘[Objectives]To develop an HPLC fingerprint analysis method for the medicinal material of Lysimachia foenum-graecum Hance,thereby providing a foundation for its quality control.[Methods]Samples of L.foenum-graecum collected from 10 distinct locations in Guangxi were analyzed using HPLC,and chromatographic fingerprints were established.The Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine(2012 Edition)was employed for common peak calibration and similarity evaluation.Additionally,principal component analysis was performed on the common peak area data.[Results]An HPLC fingerprint of L.foenum-graecum was developed,identifying a total of 13 common peaks.Among these,four characteristic components were specifically identified:chlorogenic acid,myricetin,quercetin,and kaempferol.The kaempferol chromatographic peak,exhibiting good resolution and a stable peak shape,was selected as the reference peak.The similarity indices between the fingerprints of the 10 sample batches and the reference fingerprint ranged from 0.954 to 0.995,indicating a relatively high consistency in the chemical composition of L.foenum-graecum from different origins.Principal component analysis identified two principal components,which together accounted for 89.45%of the cumulative variance,effectively capturing the primary chemical differences among the samples.[Conclusions]The established HPLC fingerprint method is straightforward to implement,stable,reliable,and exhibits high specificity.When combined with similarity evaluation and principal component analysis,it offers a scientific basis for developing quality standards for L.foenum-graecum medicinal materials.
基金supported by Korea Institute of Police Technology(KIPoT)grant funded by the Korea government(KNPA)(Project Name:Development of Lv.4 Driving Ability Evaluation Technology for Autonomous Vehicles Based on Real Roads/Project Number:RS-2023-00238253).
文摘Analyzing the driving behavior of autonomous vehicles(AV)in mixed traffic conditions at urban intersections has become increasingly important for improving intersection design,providing infrastructure-based guidance information,and developing capability-enhanced AV perception systems.This study investigated the contributing factors affecting AV driving behavior using theWaymo Open Dataset.Binarized autonomous driving stability metrics,derived via a kernel density estimation,served as the target variables for a random forest classification model.The model’s input variables included 15 factors divided into four types:intersection-related,surrounding object-related,road infrastructure-related,and time-of-day-related types.The random forest classification model was employed to identify the key factors affecting autonomous driving behavior.In addition,the identified factors were further ranked based on feature importance.SHAP analysis was utilized to enhance model interpretability by quantifying the contribution of each factor and identifying their directional impacts.The type of intersection factor was found to have an importance of 0.243 and was the most influential factor on autonomous driving behavior.On average,intersection-related factors had an importance of 0.196,which is approximately a 31.1%margin over the average importance of surrounding object-related factors.Additionally,the surrounding object-related factors that were collected through sensors on the autonomous vehicle had a high degree of feature importance,especially with the number of pedestrians having the highest importance(0.107)of the types of objects.The correlation between these findings can contribute to the development of various treatments to improvemore harmonized AVs’maneuvering with other road users and facilities in urban mixed traffic environments.
基金Supported by Jiangxi Education Department Project(GJJ201533)University-level Project of Gannan Medical University(YB201902).
文摘[Objectives]This study was conducted to isolate and identify the components from stems of Polyalthia plagioneura.[Methods]The compounds were isolated and purified by silica gel column,Sephadex LH-20,and C_(18) chromatography.Their chemical structures were elucidated on the basis of physicochemical properties and spectral data.[Results]Five compounds were isolated and identified as:di(2-ethylhexyl)phthalate(1),cinnamic anhydride(2),phthalic acid(3),citric acid(4),and syringaldehyde(5).[Conclusions]All compounds were isolated from this plant for the first time.
基金supported by the GRRC program of Gyeonggi province[GRRC KGU 2023-B01,Research on Intelligent Industrial Data Analytics].
文摘Predictive maintenance(PdM)is vital for ensuring the reliability,safety,and cost efficiency of heavyduty vehicle fleets.However,real-world sensor data are often highly imbalanced,noisy,and temporally irregular,posing significant challenges to model robustness and deployment.Using multivariate time-series data from Scania trucks,this study proposes a novel PdM framework that integrates efficient feature summarization with cost-sensitive hierarchical classification.First,the proposed last_k_summary method transforms recent operational records into compact statistical and trend-based descriptors while preserving missingness,allowing LightGBM to leverage its inherent split rules without ad-hoc imputation.Then,a two-stage LightGBM framework is developed for fault detection and severity classification:Stage A performs safety-prioritized fault screening(normal vs.fault)with a false-negativeweighted objective,and Stage B refines the detected faults into four severity levels through a cascaded hierarchy of binary classifiers.Under the official cost matrix of the IDA Industrial Challenge,the framework achieves total misclassification costs of 36,113(validation)and 36,314(test),outperforming XGBoost and Bi-LSTM by 3.8%-13.5%while maintaining high recall for the safety-critical class(0.83 validation,0.77 test).These results demonstrate that the proposed approach not only improves predictive accuracy but also provides a practical and deployable PdM solution that reduces maintenance cost,enhances fleet safety,and supports data-driven decision-making in industrial environments.
文摘Ulva lactuca whole components served as a carbon source for high-density fermentation of Bifidobacterium,yielding a low-cost,highly biocompatible Ulva lactuca bifidobacterium ferment filtrate(ULBFF).Its peptide profile and molecular weight distribution were characterized by LC/MS.Cosmetic potential was systematically evaluated through stability testing,HET-CAM test,ABTS+∙/DPPH∙scavenging,NO inhibition,melanin suppression,and type Ⅰ collagen promotion.The results indicated a rich distribution of peptides,predominantly low-molecular-weight oligopeptides,with 92.92%of peptides containing≤20 amino acids and 84.89%of components having a molecular weight<500 Da.Formulations exhibited excellent stability and low irritation.Furthermore,they showed significantly enhanced efficacy in key areas,including antioxidant and antiinflammatory activity,melanin suppression,and collagen promotion.The ULBFF improved multifunctional performance while maintaining formulation stability and safety,demonstrating high scalability and potential for marine bioresource utilization in functional cosmetics.
基金supported by National Key Technolo-gy R&D Program of China(2023YFD1701505)De-velopment Projects in Anhui Province(2022107020013).
文摘Lignocellulosic biomass is the most abundant re-newable resource on Earth,boasting advan-tages such as wide avail-ability and negative car-bon emissions.Especial-ly,efficient separation of lignocellulose into cellu-lose,hemicellulose and lignin,and realizing val-orization of these compo-nents are more responsive to the development needs of biomass refinery and the green chem-istry era.This review outlines the main components of lignocellulose and briefly summerizes their utilization in chemical raw materials and energy production.It mainly focused on cur-rent advances in component separation methods of lignocellulose by organic solvents,ionic liquids and deep eutectic solvents.The design of separation methods,understanding of sepa-ration mechanisms,and optimization of reaction systems in each method are highlighted in detail.Furthermore,the ongoing challenges and future directions based on mechanism and in-dustrialization are critically discussed.Our goal is to elucidate the separation mechanisms and principles of method design,providing guidance for the development of highly efficient com-ponent separation methods of lignocellulose.
基金Supported by the Central Public-interest Scientific Institution Basal Research Fund,YSFRI,CAFS(No.20603022024016)the Central Public-interest Scientific Institution Basal Research Fund,CAFS(Nos.2023TD52,2023TD76)the earmarked fund for CARS(No.CARS-49)。
文摘Crassostrea gigas has good taste and high nutritional value;however,there are few assessments of comprehensive and panoramic analyses of the nutritional quality of the northern oyster.To study the nutritional characteristics of C.gigas from different sources(ploidy,region,size,and culture mode),C.gigas from various ploidy(diploid and triploid),regions(Rushan,Off-site fattening,and Rongcheng),sizes(small,medium,and large)and culture modes(nearshore and offshore)were selected for comparative analyses.The nutritional components(moisture,protein,fat,and mineral),flavor substances(taste amino acids,nucleotides,and succinic acid),and functional indices(eicosapentaenoic acid(EPA),docosahexaenoic acid(DHA),and taurine)of C.gigas were determined.Principal component analysis(PCA)was used to comprehensively evaluate the oysters and investigate the variations in nutritional quality.The PCA results indicate that protein,essential fatty acids,selenium,zinc,taste amino acids,taurine,EPA,and DHA were core components contributing to 82.25%of the cumulative variance,providing a more comprehensive reflection of the nutrient composition of C.gigas.The extensive quality rankings for the C.gigas were as follows:diploid>triploid,Rushan>fattening>Rongcheng,medium>large>small,and offshore>nearshore.The score rank revealed that diploid oysters of medium-size from Rushan demonstrated superior nutritional quality compared to other tested samples.This is the first comprehensive and systematic investigation of C.gigas in northern China to reveal the feature of nutrients,flavor,and functional components.The study provided data support for the culture,consumption,processing,research,and nutritional quality improvement of oyster industry.
基金supported by Major Program of National Natural Science Foundation of China(U22A20188)National Science Fund for Distinguished Young Scholars(52425504).
文摘The physicochemical properties of SUS304 foil surfaces are crucial to their applications.Pulsed laser modification was applied to 30μm thick SUS304 foils to systematically investigate the influence of laser energy on surface characteristics.Through multidimensional characterization of surface morphology,three-dimensional profiles and roughness,contact angle,and chemical composition,the structure-function correlation between laser energy and the physicochemical properties of steel surface was revealed.With increasing laser energy,the surface morphology of the steel transitions from a directional rolling-marked structure to a uniform sponge-like isotropic structure,accompanied by increased peak density and an expanded interfacial area.Additionally,the chemical state on the metal surface gradually stabilizes from unstable redox reactions,forming a stable oxide layer and significantly increasing active hydroxyl groups,thereby effectively improving surface wettability.Single lap shear tests reveal an enhancement in the bonding strength of steel/carbon fiber reinforced composites joints after laser modification,which is attributed to the synergistic effects of mechanical interlocking,enhanced wettability,and chemical bonding at the interface.The demonstrated potential of laser surface treatment for modifying SUS304 ultra-thin foils provides theoretical support and technical reference for its application in fiber metal laminates.
基金supported by University Key Lab for Geomatics Technology&Optimize Resources Utilization in Fujian Province(KJG20104A)Fujian Forestry Science and Technology project(2023FKJ15)Fuzhou Forestry Science and Technology Research Project(2130206).
文摘Accurate assessment of site quality in coastal Casuarina equisetifolia(C.equisetifolia)plantations is essential for enhancing the protective function of shelterbelts and implementing site-specific afforestation strategies.However,traditional ground-based surveys are limited in spatial coverage and efficiency,hindering effective forest management.To overcome these limitations,this study developed an integrated assessment framework that couples ground-based modeling with remote sensing inversion to achieve large-scale site quality mapping.Field investigations on Pingtan Island,Fujian Province,China,were used to establish a ground-based evaluation model.Soil fertility was quantified using Principal Component Analysis(PCA),and principal components were classified into discrete fertility grades through K-means clustering.These grades,together with topographic variables,were incorporated into a site quality classification model constructed using Quantification Theory I.The point-based model was subsequently extrapolated using Landsat 9 imagery to generate a spatially continuous site quality map.Spatial autocorrelation(Moran’s Ⅰ)and LISA clustering were further employed to interpret spatial patterns.Results indicate that coastal sandy soils in the study area are generally nutrient-poor,with tree growth primarily constrained by total nitrogen,organic matter,available phosphorus,and total phosphorus.The five most influential site factors,ranked by importance,are soil fertility,distance from the coastline,aspect,slope gradient,and elevation.Optimal conditions for C.equisetifolia growth include fertile soil,location>1000 m from the coastline,south-facing or semi-sunny slopes,slope gradients<15°,and elevations between 10-100 m.Only 11.94%of the area was classified as high-quality(Grade I),while 61.74%fell into moderate or poor grades(Grades Ⅲ and Ⅳ),indicating that most plantations are located on suboptimal sites.This study provides scientific support for improving the precision and sustainability of coastal shelterbelt planning and management,offering practical insights for afforestation strategies,forest restoration,and ecological forestry development in coastal zones.
基金supported by the Jilin Province Health Science and Technology Ability Improvement Project(2023JL057).
文摘Objective:Triple-negative breast cancer(TNBC)is highly aggressive and lacks an effective targeted therapy.This study aimed to elucidate the functions and possible mechanisms of action of zinc finger miz-type containing 2(ZMIZ2)and minichromosome maintenance complex component 3(MCM3)in TNBC progression.Methods:The relationship between ZMIZ2 expression and clinical characteristics of TNBC was investigated.In vitro and in vivo experiments were performed to investigate the role of ZMIZ2 dysregulation in TNBC cell malignant behaviors.The regulatory relationship between ZMIZ2 and MCM3 was also explored.Transcriptome sequencing was performed to elucidate possible mechanisms underlying the ZMIZ2/MCM3 axis in TNBC.Results:High ZMIZ2 expression levels were associated with the malignant degree of TNBC.ZMIZ2 overexpression promoted TNBC cell proliferation,migration,and invasion;inhibited apoptosis;and induced G1 phase cell cycle arrest,whereas knockdown of ZMIZ2 had the opposite effect.ZMIZ2 directly targeted and positively regulated MCM3 expression.MCM3 knockdown reversed the effect of ZMIZ2 overexpression on TNBC tumor growth both in vitro and in vivo.High MCM3 expression levels were linked to the degree of malignancy and poor prognosis in TNBC.The differentially expressed genes associated with the ZMIZ2/MCM3 axis were significantly enriched in multiple pathways,such as the mitogen-activated protein kinase(MAPK),mechanistic target of rapamycin(mTOR),Wnt,and Ras signaling pathways,as verified by The Cancer Genome Atlas data.Conclusions:ZMIZ2 and MCM3 were highly expressed in TNBC.ZMIZ2 promoted the development by positively regulating MCM3 expression.Key pathways,such as the Ras/MAPK,phosphatidylinositol 3-kinase(PI3K)/protein kinase B(AKT)/mTOR,and Wnt signaling pathways,may be key downstreammechanisms.
