In the face of the increasingly serious electromagnetic wave (EMW) pollution, a component modulation strategy is proposed in this study. By integrating ZIF-67 and FeOOH into MXene nanosheets and performing heat treatm...In the face of the increasingly serious electromagnetic wave (EMW) pollution, a component modulation strategy is proposed in this study. By integrating ZIF-67 and FeOOH into MXene nanosheets and performing heat treatment, a multiphase heterogeneous structure based on the multicomponent synergistic effect was successfully constructed. The synergistic effect of dielectric loss and magnetic loss is realized, and the rich heterogeneous interface and multi-scale structure significantly enhance the interface polarization and multiple scattering. The results show that the EMW absorption performance can be optimized by adjusting the composition of the composites. MXene@CoFe_(2)O_(4) exhibits a minimum reflection loss (RLmin) of -44.98 dB at 2.3 mm thickness and a maximum effective absorption bandwidth (EAB_(max)) of 4.64 GHz at 2.1 mm. MXene@CoFe_(2)O_(4)/CoFe composite has an RLmin of -55.14 dB at a thickness of 2.1 mm and an EAB_(max) of 5.60 GHz at a thickness of 1.9 mm. This work provides important insights into the development of wideband EMW absorbent materials.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
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
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
[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
The commercial AM60(Mg−6Al−0.3Mn)die-casting alloy was modified through Mn,Ce,and La micro-alloying,each at a content below 0.2 wt.%.SEM,TEM,and Micro-CT were employed to characterize the microstructures and propertie...The commercial AM60(Mg−6Al−0.3Mn)die-casting alloy was modified through Mn,Ce,and La micro-alloying,each at a content below 0.2 wt.%.SEM,TEM,and Micro-CT were employed to characterize the microstructures and properties of AM60 based alloys.AM60-0.2La alloy showed excellent mechanical properties.The ultimate tensile strength,yield strength,and elongation of(288.0±1.7)MPa,(158.0±1.0)MPa,and(22.0±3.0)%were achieved in AM60-0.2La alloy.Besides,AM60-0.2La alloy exhibited the best corrosion resistance(0.29 mm/a)and fluidity among the investigated four alloys.The excellent mechanical properties and corrosion resistance are mainly attributed to the grain refinement strengthening,low porosity,and low content of large shrinkage porosity,promising for super-sized integrated automotive components.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
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
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
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
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
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
To investigate the evolution of grain orientation and slip modes in magnesium alloys with multiple texture components,an AZ31 gradient-structured magnesium alloy sheet was fabricated using hard plate rolling(HPR).The ...To investigate the evolution of grain orientation and slip modes in magnesium alloys with multiple texture components,an AZ31 gradient-structured magnesium alloy sheet was fabricated using hard plate rolling(HPR).The changes in texture and slip modes under different reductions were examined.The results demonstrate that the AZ31 magnesium alloy sheets display a self-epitaxial gradient structure,with the best mechanical properties observed at rolling temperature of 673 K and reduction of 50%.Significant changes in texture type and strength are observed along the normal direction(ND)of the sheet.The coarse-grain region exhibits a bimodal texture aligned with the rolling direction.These texture variations enhance the stress distribution at the fine grain-coarse grain interface,influencing the grain orientation and the activation of different slip modes,thus improving the mechanical properties of gradient-structured magnesium alloy sheets.This approach offers a new strategy for the fabrication of high-performance magnesium alloy sheets.展开更多
Background:Modified Qiangli Dingxuan Tablets(ZYSJ)is an optimized formulation derived from the classic Chinese patent medicine Qiangli Dingxuan Tablet.It targets the pathological features associated with metabolic hyp...Background:Modified Qiangli Dingxuan Tablets(ZYSJ)is an optimized formulation derived from the classic Chinese patent medicine Qiangli Dingxuan Tablet.It targets the pathological features associated with metabolic hypertension(MH)and metabolic disorders,although its antihypertensive mechanism remains unclear.Methods:A rat model of metabolic hypertension was established using a high-sugar,high-fat diet combined with progressively increasing concentrations of ethanol.Blood pressure,serum lipids,inflammatory cytokines,and endothelial function markers were assessed.Serum pharmacochemistry combined with network pharmacology was employed to predict key targets and pathways,followed by in vivo validation using qRT-PCR,Western blotting,immunofluorescence,and immunohistochemistry.Results:ZYSJ significantly reduced blood pressure and serum lipid levels in model rats.Thirty absorbed bioactive components were identified.Mechanistic studies revealed that ZYSJ downregulated the TLR4/MyD88/NF-κB signaling pathway at both the mRNA and protein levels,upregulated endothelial nitric oxide synthase(eNOS)expression,and decreased the levels of inflammatory cytokines(TNF-α,IL-1β,IL-6),thereby improving vascular endothelial function.Conclusion:ZYSJ effectively lowers blood pressure and serum lipids in rats with metabolic hypertension.Its mechanism of action is closely associated with regulation of the TLR4/MyD88/NF-κB signaling pathway,improvement of vascular endothelial function,and alleviation of inflammation.展开更多
The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measu...The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measures in a multi-family house building in Greece.The energy efficiency measures include different heating/cooling systems(such as low-temperature and high-temperature heat pumps,natural gas boilers,split units),building envelope components for floor,walls,roof and windows of variable heat transfer coefficients,the installation of solar thermal collectors and PVs.The calculations of the building loads and investment and operating and maintenance costs of the measures are based on the methodology defined in Directive 2010/31/EU,while economic assumptions are based on EN 15459-1 standard.Typically,multi-objective optimization of energy efficiency measures often requires the simulation of very large numbers of cases involving numerous possible combinations,resulting in intense computational load.The results of the study indicate that ANN-driven GA methods can be used as an alternative,valuable tool for reliably predicting the optimal measures which minimize primary energy consumption and life cycle cost of the building with greatly reduced computational requirements.Through GA methods,the computational time needed for obtaining the optimal solutions is reduced by 96.4%-96.8%.展开更多
电子元器件种类繁多且没有一致的细粒度分类标准,为快速满足元器件在不同粒度下的分类需求,提出一种基于深度学习的YOLOR-ECA(YOLOv8 and ResNet50 with efficient channel attention)电子元器件检测算法。首先采用YOLOv8网络定位元器...电子元器件种类繁多且没有一致的细粒度分类标准,为快速满足元器件在不同粒度下的分类需求,提出一种基于深度学习的YOLOR-ECA(YOLOv8 and ResNet50 with efficient channel attention)电子元器件检测算法。首先采用YOLOv8网络定位元器件位置,然后采用ResNet50网络对定位获取的元器件进行识别分类,通过元器件种类的增减满足不同细粒度的分类标准。为提升模型对尺寸小、特征相似元器件的细节特征提取能力,分类网络引入ECA注意力机制,并对残差结构的捷径连接部分进行改进;为避免神经元失活,采用GELU(Gaussian Error Linear Units)激活函数。实验结果表明,改进的YOLOR-ECA模型的检测准确率为96.6%,并且对于小尺寸元器件的识别精度最高可达100%,对于具有特征相似性元器件的误检率最低可降到0.01%,能实现电子元器件在不同细粒度分类标准下的高效检测。展开更多
In order to classify nonlinear features with a linear classifier and improve the classification accuracy, a deep learning network named kernel principal component analysis network（ KPCANet） is proposed. First, the d...In order to classify nonlinear features with a linear classifier and improve the classification accuracy, a deep learning network named kernel principal component analysis network（ KPCANet） is proposed. First, the data is mapped into a higher-dimensional space with kernel principal component analysis to make the data linearly separable. Then a two-layer KPCANet is built to obtain the principal components of the image. Finally, the principal components are classified with a linear classifier. Experimental results showthat the proposed KPCANet is effective in face recognition, object recognition and handwritten digit recognition. It also outperforms principal component analysis network（ PCANet） generally. Besides, KPCANet is invariant to illumination and stable to occlusion and slight deformation.展开更多
A novel magnetorheological finishing(MRF)process using a small ball-end permanent-magnet polishing head is proposed,and a four-axes linkage dedicated MRF machine tool is fabricated to achieve the nanofinishing of an i...A novel magnetorheological finishing(MRF)process using a small ball-end permanent-magnet polishing head is proposed,and a four-axes linkage dedicated MRF machine tool is fabricated to achieve the nanofinishing of an irregularψ-shaped small-bore complex component with concave surfaces of a curvature radius less than3 mm.The processing method of the complex component is introduced.Magnetostatic simulation during the entire finishing path is carried out to analyze the material removal characteristics.A typicalψ-shaped small-bore complex component is polished on the developed device,and a fine surface quality is obtained with surface roughness Raof 0.0107μm and surface accuracy of the finished spherical surfaces of 0.3320μm(PV).These findings indicate that the proposed MRF process can perform the nanofinishing of a kind of small-bore complex component with small-curvature-radius concave surfaces.展开更多
The correlation between the stress concentration and the spontaneous magnetic signals of metal magnetic memory(MMM) was investigated via tensile tests. Sheet specimens of the Q235 steel were machined into standard bar...The correlation between the stress concentration and the spontaneous magnetic signals of metal magnetic memory(MMM) was investigated via tensile tests. Sheet specimens of the Q235 steel were machined into standard bars with rectangular holes to obtain various stress concentration factors. The tangential component Hp(x) of MMM signals and its related magnetic characteristic parameters throughout the loading process were presented and analyzed. It is found that the tangential component Hp(x) is sensitive to the abnormal magnetic changes caused by the local stress concentration in the defect area. The minimum magnetic field is positively correlated to the magnitude of the load and the distance from the notch. The tangential magnetic stress concentration factor presents good numerical stability during the entire loading process, and can be used to evaluate the stress concentration factor. The results obtained will be a complement to the MMM technique.展开更多
基金supported by the National Nat-ural Science Foundation of China(No.52377026)the Tais-han Scholars Program(No.tsqn202103057)+6 种基金the Natural Sci-ence Foundation of Shandong Province(No.ZR2024ME046)the Postdoctoral Fellowship Program of CPSF(No.GZB20240327)the Shandong Postdoctoral Science Foundation(No.SDCX-ZG-202400275)the Qingdao Postdoctoral Application Research Project(No.QDBSH20240102023)the Postdoctoral Science Foundation of China(No.2024M751563)the Key Innovative Research Team of New Energy Materials and Devices(No.BBXYKYTDxjZD01)the University Natural Science Research Project of Anhui Province(No.2022AH010101).
文摘In the face of the increasingly serious electromagnetic wave (EMW) pollution, a component modulation strategy is proposed in this study. By integrating ZIF-67 and FeOOH into MXene nanosheets and performing heat treatment, a multiphase heterogeneous structure based on the multicomponent synergistic effect was successfully constructed. The synergistic effect of dielectric loss and magnetic loss is realized, and the rich heterogeneous interface and multi-scale structure significantly enhance the interface polarization and multiple scattering. The results show that the EMW absorption performance can be optimized by adjusting the composition of the composites. MXene@CoFe_(2)O_(4) exhibits a minimum reflection loss (RLmin) of -44.98 dB at 2.3 mm thickness and a maximum effective absorption bandwidth (EAB_(max)) of 4.64 GHz at 2.1 mm. MXene@CoFe_(2)O_(4)/CoFe composite has an RLmin of -55.14 dB at a thickness of 2.1 mm and an EAB_(max) of 5.60 GHz at a thickness of 1.9 mm. This work provides important insights into the development of wideband EMW absorbent materials.
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.
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.
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financially supported by the National Key Research and Development Program of China(Nos.2022YFB3709300,2021YFB3701000)the National Natural Science Foundation of China(Nos.52271090,52071036,U2037601,U21A2048)+1 种基金Chongqing Science and Technology Commission,China(Nos.CSTB2022TIAD-KPX0021,CSTC2024YCJHBGZXM0164,CSTB2024TIAD-KPX0001)the Fundamental Research Funds for the Central Universities,China(No.2022CDJDX-002)。
文摘The commercial AM60(Mg−6Al−0.3Mn)die-casting alloy was modified through Mn,Ce,and La micro-alloying,each at a content below 0.2 wt.%.SEM,TEM,and Micro-CT were employed to characterize the microstructures and properties of AM60 based alloys.AM60-0.2La alloy showed excellent mechanical properties.The ultimate tensile strength,yield strength,and elongation of(288.0±1.7)MPa,(158.0±1.0)MPa,and(22.0±3.0)%were achieved in AM60-0.2La alloy.Besides,AM60-0.2La alloy exhibited the best corrosion resistance(0.29 mm/a)and fluidity among the investigated four alloys.The excellent mechanical properties and corrosion resistance are mainly attributed to the grain refinement strengthening,low porosity,and low content of large shrinkage porosity,promising for super-sized integrated automotive components.
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 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.
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.
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 Natural Science Foundation of Heilongjiang Province,China(No.JQ2022E004)。
文摘To investigate the evolution of grain orientation and slip modes in magnesium alloys with multiple texture components,an AZ31 gradient-structured magnesium alloy sheet was fabricated using hard plate rolling(HPR).The changes in texture and slip modes under different reductions were examined.The results demonstrate that the AZ31 magnesium alloy sheets display a self-epitaxial gradient structure,with the best mechanical properties observed at rolling temperature of 673 K and reduction of 50%.Significant changes in texture type and strength are observed along the normal direction(ND)of the sheet.The coarse-grain region exhibits a bimodal texture aligned with the rolling direction.These texture variations enhance the stress distribution at the fine grain-coarse grain interface,influencing the grain orientation and the activation of different slip modes,thus improving the mechanical properties of gradient-structured magnesium alloy sheets.This approach offers a new strategy for the fabrication of high-performance magnesium alloy sheets.
基金supported by Natural science foundation of Zhejiang province(No.ZCLMS25H2801 to Ying-Jie Dong)Zhejiang Provincial"Vanguard"and"Leading Goose"R&D Tackling Program(No.2025C02183 to Su-Hong Chen)+1 种基金National Natural Science Foundation of China(No.82274134 to Su-Hong Chen and No.82404900 to Ying-Jie Dong)the Key Laboratory of Zhejiang Province(No.2012E10002 to Gui-Yuan Lv).
文摘Background:Modified Qiangli Dingxuan Tablets(ZYSJ)is an optimized formulation derived from the classic Chinese patent medicine Qiangli Dingxuan Tablet.It targets the pathological features associated with metabolic hypertension(MH)and metabolic disorders,although its antihypertensive mechanism remains unclear.Methods:A rat model of metabolic hypertension was established using a high-sugar,high-fat diet combined with progressively increasing concentrations of ethanol.Blood pressure,serum lipids,inflammatory cytokines,and endothelial function markers were assessed.Serum pharmacochemistry combined with network pharmacology was employed to predict key targets and pathways,followed by in vivo validation using qRT-PCR,Western blotting,immunofluorescence,and immunohistochemistry.Results:ZYSJ significantly reduced blood pressure and serum lipid levels in model rats.Thirty absorbed bioactive components were identified.Mechanistic studies revealed that ZYSJ downregulated the TLR4/MyD88/NF-κB signaling pathway at both the mRNA and protein levels,upregulated endothelial nitric oxide synthase(eNOS)expression,and decreased the levels of inflammatory cytokines(TNF-α,IL-1β,IL-6),thereby improving vascular endothelial function.Conclusion:ZYSJ effectively lowers blood pressure and serum lipids in rats with metabolic hypertension.Its mechanism of action is closely associated with regulation of the TLR4/MyD88/NF-κB signaling pathway,improvement of vascular endothelial function,and alleviation of inflammation.
文摘The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measures in a multi-family house building in Greece.The energy efficiency measures include different heating/cooling systems(such as low-temperature and high-temperature heat pumps,natural gas boilers,split units),building envelope components for floor,walls,roof and windows of variable heat transfer coefficients,the installation of solar thermal collectors and PVs.The calculations of the building loads and investment and operating and maintenance costs of the measures are based on the methodology defined in Directive 2010/31/EU,while economic assumptions are based on EN 15459-1 standard.Typically,multi-objective optimization of energy efficiency measures often requires the simulation of very large numbers of cases involving numerous possible combinations,resulting in intense computational load.The results of the study indicate that ANN-driven GA methods can be used as an alternative,valuable tool for reliably predicting the optimal measures which minimize primary energy consumption and life cycle cost of the building with greatly reduced computational requirements.Through GA methods,the computational time needed for obtaining the optimal solutions is reduced by 96.4%-96.8%.
文摘电子元器件种类繁多且没有一致的细粒度分类标准,为快速满足元器件在不同粒度下的分类需求,提出一种基于深度学习的YOLOR-ECA(YOLOv8 and ResNet50 with efficient channel attention)电子元器件检测算法。首先采用YOLOv8网络定位元器件位置,然后采用ResNet50网络对定位获取的元器件进行识别分类,通过元器件种类的增减满足不同细粒度的分类标准。为提升模型对尺寸小、特征相似元器件的细节特征提取能力,分类网络引入ECA注意力机制,并对残差结构的捷径连接部分进行改进;为避免神经元失活,采用GELU(Gaussian Error Linear Units)激活函数。实验结果表明,改进的YOLOR-ECA模型的检测准确率为96.6%,并且对于小尺寸元器件的识别精度最高可达100%,对于具有特征相似性元器件的误检率最低可降到0.01%,能实现电子元器件在不同细粒度分类标准下的高效检测。
基金The National Natural Science Foundation of China(No.6120134461271312+7 种基金6140108511301074)the Research Fund for the Doctoral Program of Higher Education(No.20120092120036)the Program for Special Talents in Six Fields of Jiangsu Province(No.DZXX-031)Industry-University-Research Cooperation Project of Jiangsu Province(No.BY2014127-11)"333"Project(No.BRA2015288)High-End Foreign Experts Recruitment Program(No.GDT20153200043)Open Fund of Jiangsu Engineering Center of Network Monitoring(No.KJR1404)
文摘In order to classify nonlinear features with a linear classifier and improve the classification accuracy, a deep learning network named kernel principal component analysis network（ KPCANet） is proposed. First, the data is mapped into a higher-dimensional space with kernel principal component analysis to make the data linearly separable. Then a two-layer KPCANet is built to obtain the principal components of the image. Finally, the principal components are classified with a linear classifier. Experimental results showthat the proposed KPCANet is effective in face recognition, object recognition and handwritten digit recognition. It also outperforms principal component analysis network（ PCANet） generally. Besides, KPCANet is invariant to illumination and stable to occlusion and slight deformation.
基金supported by the National Key Research and Development Program of China [grant number 2018YFB1107600]
文摘A novel magnetorheological finishing(MRF)process using a small ball-end permanent-magnet polishing head is proposed,and a four-axes linkage dedicated MRF machine tool is fabricated to achieve the nanofinishing of an irregularψ-shaped small-bore complex component with concave surfaces of a curvature radius less than3 mm.The processing method of the complex component is introduced.Magnetostatic simulation during the entire finishing path is carried out to analyze the material removal characteristics.A typicalψ-shaped small-bore complex component is polished on the developed device,and a fine surface quality is obtained with surface roughness Raof 0.0107μm and surface accuracy of the finished spherical surfaces of 0.3320μm(PV).These findings indicate that the proposed MRF process can perform the nanofinishing of a kind of small-bore complex component with small-curvature-radius concave surfaces.
基金Funded by the Zhejiang Provincial Natural Science Foundation of China(LZ12E08003)the Fundamental Research Funds for the Central Universities,China(2015QNA4028)
文摘The correlation between the stress concentration and the spontaneous magnetic signals of metal magnetic memory(MMM) was investigated via tensile tests. Sheet specimens of the Q235 steel were machined into standard bars with rectangular holes to obtain various stress concentration factors. The tangential component Hp(x) of MMM signals and its related magnetic characteristic parameters throughout the loading process were presented and analyzed. It is found that the tangential component Hp(x) is sensitive to the abnormal magnetic changes caused by the local stress concentration in the defect area. The minimum magnetic field is positively correlated to the magnitude of the load and the distance from the notch. The tangential magnetic stress concentration factor presents good numerical stability during the entire loading process, and can be used to evaluate the stress concentration factor. The results obtained will be a complement to the MMM technique.
