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
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
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
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
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
[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
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
Component-based Chinese Medicine(CCM)stands as a pivotal endeavor in modernizing traditional Chinese medicine(TCM).By integrating classical TCM theories with modern scientific methodologies,CCM aims to achieve herbal ...Component-based Chinese Medicine(CCM)stands as a pivotal endeavor in modernizing traditional Chinese medicine(TCM).By integrating classical TCM theories with modern scientific methodologies,CCM aims to achieve herbal formulas with“defined components,clarified mechanisms,and controllable quality.”This approach not only transitions TCM development from empirical tradition to evidence-based science but also positions it for global recognition.Drawing on recent advancements in CCM,this editorial explores key insights and challenges shaping its trajectory.展开更多
[Objectives]To establish a multi-indicator quality control method for the retention of Longqing Capsule based on the principle of prescription of Chinese medicine.[Methods]High performance liquid chromatography(HPLC)w...[Objectives]To establish a multi-indicator quality control method for the retention of Longqing Capsule based on the principle of prescription of Chinese medicine.[Methods]High performance liquid chromatography(HPLC)with ShimNex CS C 18 as the column;column temperature:35℃;wavelength:270 nm;methanol-0.1%phosphoric acid solution as the mobile phase with gradient elution.[Results]The 12 components of the retention of Longqing Capsule showed good linearity within the investigated range(r≥0.9995),with the average spiked recoveries of 97.83%-100.52%and the RSD of 0.9%-2.1%.[Conclusions]The method is exclusive,sensitive,reproducible,simple and easy to use,and can provide a reference for the construction of the quality standard and control system of Longqing Capsule based on the theory of traditional Chinese medicine.展开更多
Acupuncture,a therapeutic practice rooted in traditional Chinese medicine and integrated with modern neuroscience,achieves its effects by stimulating sensory nerves at specific anatomical points known as acupoints.Thi...Acupuncture,a therapeutic practice rooted in traditional Chinese medicine and integrated with modern neuroscience,achieves its effects by stimulating sensory nerves at specific anatomical points known as acupoints.This review systematically explores the therapeutic components of acupuncture,emphasizing the interplay between sensory nerve characteristics and neural signaling pathways.Key factors such as acupoint location,needling depth,stimulation intensity,retention time,and the induction of sensations(e.g.,Deqi)are analyzed for their roles in neural activation and clinical outcomes.The review highlights how variations in spinal segment targeting,tissue-specific receptor activation,and stimulation modalities(e.g.,manual acupuncture,electroacupuncture,moxibustion)influence therapeutic effects.Emerging evidence underscores the significance of ion channels,dermatomes,myotomes,and genespecific pathways in mediating systemic effects.Additionally,the differential roles of mechanical,thermal and nociceptive stimuli and the temporal dynamics of sensory and immune responses are addressed.While insights from animal models have advanced our understanding,their translation to clinical practice requires further investigation.This comprehensive review identifies critical parameters for optimizing acupuncture therapy,advocating for individualized treatment strategies informed by neuroanatomical and neurophysiological principles,ultimately enhancing its precision and efficacy in modern medicine.展开更多
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
In order to save manpower and time costs,and to achieve simultaneous detection of multiple animal-derived components in meat and meat products,this study used multiple nucleotide polymorphism(MNP)marker technology bas...In order to save manpower and time costs,and to achieve simultaneous detection of multiple animal-derived components in meat and meat products,this study used multiple nucleotide polymorphism(MNP)marker technology based on the principle of high-throughput sequencing,and established a multi-locus 10 animalderived components identification method of cattle,goat,sheep,donkey,horse,chicken,duck,goose,pigeon,quail in meat and meat products.The specific loci of each species could be detected and the species could be accurately identified,including 5 loci for cattle and duck,3 loci for sheep,9 loci for chicken and horse,10 loci for goose and pigeon,6 loci for quail and 1 locus for donkey and goat,and an adulteration model was established to simulate commercially available samples.The results showed that the method established in this study had high throughput,good repeatability and accuracy,and was able to identify 10 animalderived components simultaneously with 100%repeatability accuracy.The detection limit was 0.1%(m/m)in simulated samples of chicken,duck and horse.Using the method established in this study to test commercially available samples,4 samples from 14 commercially available samples were detected to be inconsistent with the labels,of which 2 did not contain the target ingredient and 2 were adulterated with small amounts of other ingredients.展开更多
Metal Additive Manufacturing(MAM) technology has become an important means of rapid prototyping precision manufacturing of special high dynamic heterogeneous complex parts. In response to the micromechanical defects s...Metal Additive Manufacturing(MAM) technology has become an important means of rapid prototyping precision manufacturing of special high dynamic heterogeneous complex parts. In response to the micromechanical defects such as porosity issues, significant deformation, surface cracks, and challenging control of surface morphology encountered during the selective laser melting(SLM) additive manufacturing(AM) process of specialized Micro Electromechanical System(MEMS) components, multiparameter optimization and micro powder melt pool/macro-scale mechanical properties control simulation of specialized components are conducted. The optimal parameters obtained through highprecision preparation and machining of components and static/high dynamic verification are: laser power of 110 W, laser speed of 600 mm/s, laser diameter of 75 μm, and scanning spacing of 50 μm. The density of the subordinate components under this reference can reach 99.15%, the surface hardness can reach 51.9 HRA, the yield strength can reach 550 MPa, the maximum machining error of the components is 4.73%, and the average surface roughness is 0.45 μm. Through dynamic hammering and high dynamic firing verification, SLM components meet the requirements for overload resistance. The results have proven that MEM technology can provide a new means for the processing of MEMS components applied in high dynamic environments. The parameters obtained in the conclusion can provide a design basis for the additive preparation of MEMS components.展开更多
Joint roughness coefficient(JRC)is the most commonly used parameter for quantifying surface roughness of rock discontinuities in practice.The system composed of multiple roughness statistical parameters to measure JRC...Joint roughness coefficient(JRC)is the most commonly used parameter for quantifying surface roughness of rock discontinuities in practice.The system composed of multiple roughness statistical parameters to measure JRC is a nonlinear system with a lot of overlapping information.In this paper,a dataset of eight roughness statistical parameters covering 112 digital joints is established.Then,the principal component analysis method is introduced to extract the significant information,which solves the information overlap problem of roughness characterization.Based on the two principal components of extracted features,the white shark optimizer algorithm was introduced to optimize the extreme gradient boosting model,and a new machine learning(ML)prediction model was established.The prediction accuracy of the new model and the other 17 models was measured using statistical metrics.The results show that the prediction result of the new model is more consistent with the real JRC value,with higher recognition accuracy and generalization ability.展开更多
AIM To investigate the material basis and mechanism underlying the therapeutic effect of DLC in T2DM.METHODS T2DM was triggered in rats using a high-sugar,high-fat diet alongside 35 mg/kg streptozotocin.The effect of ...AIM To investigate the material basis and mechanism underlying the therapeutic effect of DLC in T2DM.METHODS T2DM was triggered in rats using a high-sugar,high-fat diet alongside 35 mg/kg streptozotocin.The effect of DLC on the intestinal microbiota in T2DM rats was analyzed via 16S rDNA sequencing.Targeted metabolomics was conducted to evaluate the impact of DLC on the levels of nine short-chain fatty acids(SCFAs).Untargeted metabolomics examined DLC-induced alterations in fecal metabolites and associated metabolic pathways.Additionally,Spearman’s correlation analysis assessed gut microbiota and fecal metabolite relationships.RESULTS DLC significantly attenuated pathological weight loss,reduced fasting blood glucose levels,restored blood sugar homeostasis,and ameliorated dyslipidemia in T2DM rats.The 16S rDNA sequencing revealed that DLC enhanced microbial diversity and reversed intestinal dysbiosis.Targeted metabolomics indicated decreased acetic acid and propionic acid levels and increased butyric acid,isobutyric acid,and 2-methylbutyric acid levels after DLC treatment.Untargeted metabolomics revealed 57 metabolites with altered expression associated with amino acid,carbohydrate,purine,and biotin pathways.The Spearman analysis demonstrated significant links between specific gut microbiota taxa and fecal metabolites.CONCLUSION DLC may exert hypoglycemic effects by modulating intestinal flora genera,SCFA levels,and fecal metabolites.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.
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.
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.
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 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 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.
文摘Component-based Chinese Medicine(CCM)stands as a pivotal endeavor in modernizing traditional Chinese medicine(TCM).By integrating classical TCM theories with modern scientific methodologies,CCM aims to achieve herbal formulas with“defined components,clarified mechanisms,and controllable quality.”This approach not only transitions TCM development from empirical tradition to evidence-based science but also positions it for global recognition.Drawing on recent advancements in CCM,this editorial explores key insights and challenges shaping its trajectory.
基金Supported by Provincial University Scientific Research Platform Team Project of Guizhou Provincial Department of Education(Qianjiaoji[2022]No.010).
文摘[Objectives]To establish a multi-indicator quality control method for the retention of Longqing Capsule based on the principle of prescription of Chinese medicine.[Methods]High performance liquid chromatography(HPLC)with ShimNex CS C 18 as the column;column temperature:35℃;wavelength:270 nm;methanol-0.1%phosphoric acid solution as the mobile phase with gradient elution.[Results]The 12 components of the retention of Longqing Capsule showed good linearity within the investigated range(r≥0.9995),with the average spiked recoveries of 97.83%-100.52%and the RSD of 0.9%-2.1%.[Conclusions]The method is exclusive,sensitive,reproducible,simple and easy to use,and can provide a reference for the construction of the quality standard and control system of Longqing Capsule based on the theory of traditional Chinese medicine.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.NRF-2020R1C1C1004107)。
文摘Acupuncture,a therapeutic practice rooted in traditional Chinese medicine and integrated with modern neuroscience,achieves its effects by stimulating sensory nerves at specific anatomical points known as acupoints.This review systematically explores the therapeutic components of acupuncture,emphasizing the interplay between sensory nerve characteristics and neural signaling pathways.Key factors such as acupoint location,needling depth,stimulation intensity,retention time,and the induction of sensations(e.g.,Deqi)are analyzed for their roles in neural activation and clinical outcomes.The review highlights how variations in spinal segment targeting,tissue-specific receptor activation,and stimulation modalities(e.g.,manual acupuncture,electroacupuncture,moxibustion)influence therapeutic effects.Emerging evidence underscores the significance of ion channels,dermatomes,myotomes,and genespecific pathways in mediating systemic effects.Additionally,the differential roles of mechanical,thermal and nociceptive stimuli and the temporal dynamics of sensory and immune responses are addressed.While insights from animal models have advanced our understanding,their translation to clinical practice requires further investigation.This comprehensive review identifies critical parameters for optimizing acupuncture therapy,advocating for individualized treatment strategies informed by neuroanatomical and neurophysiological principles,ultimately enhancing its precision and efficacy in modern medicine.
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financially supported by National Key R&D Program(2021YFF0701905)。
文摘In order to save manpower and time costs,and to achieve simultaneous detection of multiple animal-derived components in meat and meat products,this study used multiple nucleotide polymorphism(MNP)marker technology based on the principle of high-throughput sequencing,and established a multi-locus 10 animalderived components identification method of cattle,goat,sheep,donkey,horse,chicken,duck,goose,pigeon,quail in meat and meat products.The specific loci of each species could be detected and the species could be accurately identified,including 5 loci for cattle and duck,3 loci for sheep,9 loci for chicken and horse,10 loci for goose and pigeon,6 loci for quail and 1 locus for donkey and goat,and an adulteration model was established to simulate commercially available samples.The results showed that the method established in this study had high throughput,good repeatability and accuracy,and was able to identify 10 animalderived components simultaneously with 100%repeatability accuracy.The detection limit was 0.1%(m/m)in simulated samples of chicken,duck and horse.Using the method established in this study to test commercially available samples,4 samples from 14 commercially available samples were detected to be inconsistent with the labels,of which 2 did not contain the target ingredient and 2 were adulterated with small amounts of other ingredients.
基金funded by the National Natural Science Foundation of China Youth Fund(Grant No.62304022)Science and Technology on Electromechanical Dynamic Control Laboratory(China,Grant No.6142601012304)the 2022e2024 China Association for Science and Technology Innovation Integration Association Youth Talent Support Project(Grant No.2022QNRC001).
文摘Metal Additive Manufacturing(MAM) technology has become an important means of rapid prototyping precision manufacturing of special high dynamic heterogeneous complex parts. In response to the micromechanical defects such as porosity issues, significant deformation, surface cracks, and challenging control of surface morphology encountered during the selective laser melting(SLM) additive manufacturing(AM) process of specialized Micro Electromechanical System(MEMS) components, multiparameter optimization and micro powder melt pool/macro-scale mechanical properties control simulation of specialized components are conducted. The optimal parameters obtained through highprecision preparation and machining of components and static/high dynamic verification are: laser power of 110 W, laser speed of 600 mm/s, laser diameter of 75 μm, and scanning spacing of 50 μm. The density of the subordinate components under this reference can reach 99.15%, the surface hardness can reach 51.9 HRA, the yield strength can reach 550 MPa, the maximum machining error of the components is 4.73%, and the average surface roughness is 0.45 μm. Through dynamic hammering and high dynamic firing verification, SLM components meet the requirements for overload resistance. The results have proven that MEM technology can provide a new means for the processing of MEMS components applied in high dynamic environments. The parameters obtained in the conclusion can provide a design basis for the additive preparation of MEMS components.
基金funding from the National Natural Science Foundation of China (Grant No.42277175)the pilot project of cooperation between the Ministry of Natural Resources and Hunan Province“Research and demonstration of key technologies for comprehensive remote sensing identification of geological hazards in typical regions of Hunan Province” (Grant No.2023ZRBSHZ056)the National Key Research and Development Program of China-2023 Key Special Project (Grant No.2023YFC2907400).
文摘Joint roughness coefficient(JRC)is the most commonly used parameter for quantifying surface roughness of rock discontinuities in practice.The system composed of multiple roughness statistical parameters to measure JRC is a nonlinear system with a lot of overlapping information.In this paper,a dataset of eight roughness statistical parameters covering 112 digital joints is established.Then,the principal component analysis method is introduced to extract the significant information,which solves the information overlap problem of roughness characterization.Based on the two principal components of extracted features,the white shark optimizer algorithm was introduced to optimize the extreme gradient boosting model,and a new machine learning(ML)prediction model was established.The prediction accuracy of the new model and the other 17 models was measured using statistical metrics.The results show that the prediction result of the new model is more consistent with the real JRC value,with higher recognition accuracy and generalization ability.
基金Supported by the National Natural Science Foundation of China,No.82160771NATCM's Project of High-Level Construction of Key TCM Disciplines:Traditional Medicine of Chinese Minority(Zhuang Medicine),No.zyyzdxk-2023165+7 种基金Guangxi One Thousand Young and Middle-Aged College and University Backbones Teachers Cultivation Program,No.[2019]5Guangxi Traditional Chinese Medicine Multidisciplinary Cross Innovation Team Project,No.GZKJ2309Guangxi Key R&D Plan Project,No.AB21196016Guangxi Key Discipline of Traditional Chinese Medicine Zhuang Pharmacy,No.GZXK-Z-20-64The First-Class Subject of Traditional Chinese Medicine(Ethnic Pharmacy)in Guangxi,No.[2018]12Guangxi Science and Technology Base and Talent Special Project,No.AD20238058 and No.AD21238031the Third Batch of Cultivating High-level Talent Teams in the“Qi Huang Project”of the Guangxi University of Chinese Medicine,No.202406and Huang Danian Style Teacher Team From Universities in Guangxi Zhuang Autonomous Region“Traditional Chinese Medicine Inheritance and Innovation Teacher Team”,No.[2023]31.
文摘AIM To investigate the material basis and mechanism underlying the therapeutic effect of DLC in T2DM.METHODS T2DM was triggered in rats using a high-sugar,high-fat diet alongside 35 mg/kg streptozotocin.The effect of DLC on the intestinal microbiota in T2DM rats was analyzed via 16S rDNA sequencing.Targeted metabolomics was conducted to evaluate the impact of DLC on the levels of nine short-chain fatty acids(SCFAs).Untargeted metabolomics examined DLC-induced alterations in fecal metabolites and associated metabolic pathways.Additionally,Spearman’s correlation analysis assessed gut microbiota and fecal metabolite relationships.RESULTS DLC significantly attenuated pathological weight loss,reduced fasting blood glucose levels,restored blood sugar homeostasis,and ameliorated dyslipidemia in T2DM rats.The 16S rDNA sequencing revealed that DLC enhanced microbial diversity and reversed intestinal dysbiosis.Targeted metabolomics indicated decreased acetic acid and propionic acid levels and increased butyric acid,isobutyric acid,and 2-methylbutyric acid levels after DLC treatment.Untargeted metabolomics revealed 57 metabolites with altered expression associated with amino acid,carbohydrate,purine,and biotin pathways.The Spearman analysis demonstrated significant links between specific gut microbiota taxa and fecal metabolites.CONCLUSION DLC may exert hypoglycemic effects by modulating intestinal flora genera,SCFA levels,and fecal metabolites.
