Grey Entropy Research Articles

Analysis and evaluation of bioactive constituents from different parts of Epimedium brevicornum

A comprehensive analytical method based on ultra-fast liquid chromatography coupled with triple quadrupole/linear ion trap tandem mass spectrometry(UFLC-QTRAP-MS/MS) was established for simultaneous determination of the content of 45 bioactive constituents including flavonoids, alkaloids, amino acids, phenolic acids, and nucleosides in Epimedium brevicornum. The multiple bioactive constituents in leaves, petioles, stems and rhizomes of E. brevicornum were analyzed. The gradient elution was performed at 30 ℃ in an XBridge~® C_(18) column(4.6 mm×100 mm, 3.5 μm) with 0.4% formic acid aqueous solution-acetonitrile as the mobile phase at a flow rate of 0.8 mL·min~(-1). Single factor experiment and response surface methodology were employed to optimize the extraction conditions. Multivariate statistical analyses including systematic cluster analysis(SCA), principal component analysis(PCA), partial least squares discriminant analysis(PLS-DA), and one-way analysis of variance(One-way ANOVA) were carried out to classify the samples from different parts and identify different constituents. Grey relation analysis(GRA) and entropy weight-TOPSIS analysis were performed to build a multi-index comprehensive evaluation model for different parts of E. brevicornum. The results showed that there was a good relationship between the mass concentrations of 45 constituents and the corresponding peak areas, with the correlation coefficients(r) not less than 0.999 0. The precision, repeatability, and stability of the established method were good for all the target constituents in this study, with the relative standard deviations(RSDs) less than 5.0%(0.62%-4.9%) and the average recovery of 94.51%-105.7%. The above results indicated that the bioactive constituents varied in different parts of E. brevicornum, and the overall quality followed the trend of leaves > petioles > rhizomes > stems. This study verified the rationality of the Chinese Pharmacopoeia(2020 edition) stipulating that the medicinal part of E. brevicornum is the leaf. Moreover, our study indicated that the rhizome had the potential for medicinal development. The established method was accurate and reliable, which can be used to comprehensive evaluate and control the quality of E. brevicornum. This study provides data reference for clarifying the medicinal parts and rationally utilizing the resources of E. brevicornum.

Crashworthiness analysis and multi-objective optimization of spatial lattice structure under dynamic compression

A spatial lattice structure is proposed to improve the structural crashworthiness and energy absorption. First, a single-cell structure is proposed via a bionic honeycomb, and then the single-cell structure is arrayed to form a spatial lattice structure. The finite element model of the spatial lattice structure for crashworthiness analysis is established. The theoretical model of the plateau stress of the lattice structure under compressive conditions is derived, and its accuracy is verified by the corresponding finite element analysis. After that, the effect of geometrical parameters of single-cell structure on crashworthiness is analyzed. Then, geometrical parameters of single-cell structure and number of single-cell in the X, Y, and Z directions are used as design variables, the mass, and overall size are used as constraints, and specific energy absorption and collision peak force are used as optimization objectives. The multi-objective crashworthiness optimization of spatial lattice structure is carried out, and the optimal lattice structure design is determined via the gray relational analysis coupling entropy weight method. The validity of the finite element model and optimal design is verified by the drop weight impact test. The crashworthiness optimization of spatial lattice structures has important guiding significance for the design of energy-absorbing structures.

Process safety assessment and thermal stability influence study on activation energy from four series of TNT based high explosives via grey entropy model

Process safety assessment and thermal stability influence study on activation energy from four series of TNT based high explosives via grey entropy model

Dynamic Evaluation of the Degradation Process of Vibration Performance for Machine Tool Spindle Bearings.

Real-time condition monitoring and fault diagnosis of spindle bearings are critical to the normal operation of the matching machine tool. In this work, considering the interference of random factors, the uncertainty of the vibration performance maintaining reliability (VPMR) is introduced for machine tool spindle bearings (MTSB). The maximum entropy method and Poisson counting principle are combined to solve the variation probability, so as to accurately characterize the degradation process of the optimal vibration performance state (OVPS) for MTSB. The dynamic mean uncertainty calculated using the least-squares method by polynomial fitting, fused into the grey bootstrap maximum entropy method, is utilized to evaluate the random fluctuation state of OVPS. Then, the VPMR is calculated, which is used to dynamically evaluate the failure degree of accuracy for MTSB. The results show that the maximum relative errors between the estimated true value and the actual value of the VPMR are 6.55% and 9.91%, and appropriate remedial measures should be taken before 6773 min and 5134 min for the MTSB in Case 1 and Case 2, respectively, so as to avoid serious safety accidents that are caused by the failure of OVPS.

A novel hybrid approach GREG-fuzzy-GA for minimizing work piece temperature during 2.5D milling of Inconel625 super alloy

PurposeMilling is a flexible creation process for the manufacturing of dies and aeronautical parts. While machining thin-walled parts, heat generation during machining essentially affects the accuracy. The workpiece temperature (WT), as well as the responses like material removal rate (MRR) and surface roughness (SR) for input parameters like cutting speed (CS), feed rate (F), depth-of-cut (DOC), step over (SO) and tool diameter (TD), becomes critical for sustaining the accuracy of the thin walls.Design/methodology/approachResponse surface methodology was used to make 46 tests. To convert the multi-character problem into a single-character problem, the weightage was assessed using the entropy approach and the grey relational coefficient (GRC) was determined. To investigate the connection among input parameters and single-objective (GRC), a fuzzy mathematical modelling technique was used. The optimal performance of process parameters was estimated by grey relational entropy grade (GREG)-fuzzy and genetic algorithm (GA) optimization.FindingsSR was found to be a significant process parameter, with CS, feed and DOC, respectively. Similarly, F, DOC and TD were found to be significant process parameters with MRR, respectively, and F, DOC, SO and TD were found to be significant process parameters with WT, respectively. GREG-fuzzy-GA found more suitable for minimizing the WT with the constraint s of SR and MRR and provide maximum desirability of 0.665. The projected and experimental values have a good agreement, with a standard error of 5.85%, and so the responses predicted by the suggested method are better optimized.Originality/valueThe GREG-fuzzy-GA is a new hybrid technique for analysing Inconel625 behaviour during machining in a 2.5D milling process.

Effect of dry-wet cycles on mechanical properties of polyurethane porous mixture

ABSTRACT Polyurethane porous mixture (PUPM) is a novel material with potential to extend the service life of pervious pavement. The porous structure makes the interior of the pavement material inevitably exposed to frequent cyclic action of environmental factors. However, the mechanical property decay behaviour of PUPM under the dry-wet cycles formed by water, air and corrosive ions is still unclear. Therefore, the mechanical properties of PUPM under different dry-wet cycles were characterised by Marshall stability, splitting strength and uniaxial compression strength tests. The variations in the microscopic properties of PUPM were investigated by computed tomography (CT), scanning electron microscopy (SEM) and Fourier transform infrared (FT-IR) spectroscopy. The grey entropy correlation theory was used to analyse the effect of variations in the functional groups of polyurethane on the mechanical properties of PUPM. It was concluded that the ageing of the polyurethane and the disruption of the bond at the binder-aggregate interface are the fundamental reasons for the mechanical property decay of PUPM. The influence of each functional group on the mechanical strength of the PUPM is in this descending order: amino groups linked to the carbonyl groups, carbonyl groups, ether bonds, methylene groups, and amino groups formed hydrogen bonds with water.

Mechanical properties and micro mechanism of alkali-activated tannery sludge/fly ash composite cement-based recycled concrete

In order to alleviate the environmental degradation and resource waste caused by cement production and construction waste disposal, some cement is replaced by tannery sludge and fly ash, and natural aggregate is replaced by recycled coarse aggregate. The preparation of alkali activated tannery sludge/fly ash composite cement-based recycled concrete (AA-SFRC) is of great significance for the safe disposal and utilization of solid waste. In order to study the mechanism of the effect of alkali-activator on the mechanical properties and microstructure of AA-SFRC, six kinds of AA-SFRC with different alkali equivalents (AE) were designed, and the strength tests, nuclear magnetic resonance (NMR), X-ray diffraction (XRD) and scanning electron microscopy (SEM) tests were carried out. On this basis, the influence of AA-SFRC pore structure parameters on strength performance was discussed by using grey entropy analysis method, and a grey model GM (1, 5) prediction model of 28d strength was established. The results demonstrated that with the increase of AE, the AA-SFRC strength increased at first and then decreased, and the tension–compression ratio (Ts/Cs) remained in the normal range, between 0.065 and 0.081. When the AE was 9%, the mineral composition of AA-SFRC reached equilibrium, and the hydration reaction was the most sufficient. The compressive strength and splitting tensile strength reached the maximum. Meanwhile, the pore structure showed that the porosity and the proportion of macro pores were the smallest. The 28d strength of AA-SFRC was greatly affected by its 7d strength, first peak ratio, fractal dimension Dmax and porosity. The average relative errors between the predicted value of GM (1, 5) model and the experimental value were less than 0.03%. This study can provide a reference for the resource utilization of tannery sludge, fly ash and construction waste.

Radiomics analysis of bone marrow biopsy locations in [18F]FDG PET/CT images for measurable residual disease assessment in multiple myeloma

The combination of visual assessment of whole body [18F]FDG PET images and evaluation of bone marrow samples by Multiparameter Flow Cytometry (MFC) or Next-Generation Sequencing (NGS) is currently the most common clinical practice for the detection of Measurable Residual Disease (MRD) in Multiple Myeloma (MM) patients. In this study, radiomic features extracted from the bone marrow biopsy locations are analyzed and compared to those extracted from the whole bone marrow in order to study the representativeness of these biopsy locations in the image-based MRD assessment. Whole body [18F]FDG PET of 39 patients with newly diagnosed MM were included in the database, and visually evaluated by experts in nuclear medicine. A methodology for the segmentation of biopsy sites from PET images, including sternum and posterior iliac crest, and their subsequent quantification is proposed. First, starting from the bone marrow segmentation, a segmentation of the biopsy sites is performed. Then, segmentations are quantified extracting SUV metrics and radiomic features from the [18F]FDG PET images and are evaluated by Mann–Whitney U-tests as valuable features differentiating PET+/PET− and MFC+ /MFC− groups. Moreover, correlation between whole bone marrow and biopsy sites is studied by Spearman ρ rank. Classification performance of the radiomics features is evaluated applying seven machine learning algorithms. Statistical analyses reveal that some images features are significant in PET+/PET− differentiation, such as SUVmax, Gray Level Non-Uniformity or Entropy, especially with a balanced database where 16 of the features show a p value < 0.001. Correlation analyses between whole bone marrow and biopsy sites results in significant and acceptable coefficients, with 11 of the variables reaching a correlation coefficient greater than 0.7, with a maximum of 0.853. Machine learning algorithms demonstrate high performances in PET+/PET− classification reaching a maximum AUC of 0.974, but not for MFC+/MFC− classification. The results demonstrate the representativeness of sample sites as well as the effectiveness of extracted features (SUV metrics and radiomic features) from the [18F]FDG PET images in MRD assessment in MM patients.

Multi-objective crashworthiness optimization of energy-absorbing box with gradient lattice structure

To improve the lightweight and crashworthiness of energy-absorbing box, an energy-absorbing box with spatial lattice structure and multi-objective optimization method are proposed. First, a novel single-cell structure is proposed, which is replicated and arranged to form the spatial lattice structure. Then, the mechanical properties of the material are tested by quasi-static and high-speed tensile tests. The finite element model of the spatial lattice structure is established, and the numerical results are verified by the drop weight impact test. Finally, four different types of approximate models are used to fit different responses, and the combination of approximate models with higher accuracy is obtained. And the multi-objective optimization of our model is carried out. The optimal design of our model is obtained based on the grey relational analysis coupling entropy weight method. Compared with the energy-absorbing box with initial lattice, the specific energy absorption of the optimal design of our model is increased from 6.23kJ/kg to 8.91kJ/kg, an increase of 43.0%, and the mass is reduced from 1.1kg to 0.798kg, a reduction of 27.4%. The results show that the optimal design of our model has the advantages of lightweight and energy absorption.

Evaluation of inducing activity of CIP elicitors from diverse sources based on monosaccharide composition and physiological indicators

Application of elicitors can greatly enhance plant immune resistance against pathogens. However, it is still obscure whether elicitor activity is influenced by diverse sources. This study investigated the effect of foliar spraying of 19 batches of Chrysanthemum indicum polysaccharides (CIPs) on the disease resistance of Atractylodes macrocephala Koidz. (A. macrocephala) and explored the main reasons for the differences of inducing activity of CIP elicitors. PCA, OPLS-DA, grey relational analysis and entropy weight method had good predictability for the activity evaluation of CIP elicitors and other plant-derived elicitors. The results showed that 19 batches of CIPs had definite regional differences in inducing activity and monosaccharide content. CIP elicitors with high inducing activity could significantly increase the accumulation of Atractylenolide Ⅱ and Atractylenolide Ⅲ, the mRNA relative transcription level of CAT, POD, PAL genes, the amount of pH change in the medium and effectively reduce the disease index of A. macrocephala. Furthermore, CIP with high inducing activity exhibited the high contents of Rha, Ara and GalA, which might be the main contributor to their high activity. The evaluation procedure developed in this work can be applied for screening CIP elicitors with high inducing activity, and it lays a foundation for identifying more functional elicitors related to plant immune resistance.

Prediction and evaluation the moisture damage resistance of rejuvenated asphalt mixtures based on neural network

The aim of this paper is to establish a model for predicting the moisture damage resistance of the rejuvenated asphalt mixture. Based on the surface free energy theory, the contact angels between asphalt and aggregate were measured with known reagents using the sessile drop method. The adhesion work, spalling work and moisture damage resistance index of the asphalt-aggregate interface system were then calculated. Secondly, the tensile strength ratio of the rejuvenated asphalt mixture was determined, and the influence of six indices, including RAP content, rejuvenator content, adhesion work, spalling work, per cent air voids in bituminous mixtures (VV) and freeze–thaw cycle on the performance of the moisture damage resistance of rejuvenated asphalt mixture was analyzed using the gray correlation entropy method. Finally, a three-layer neural network was used to predict the moisture damage resistance of the rejuvenated asphalt mixture. The results show that as the content of aged asphalt increases, the adhesion work of the asphalt- aggregate interface system decreases. Furthermore, for the system of the same rejuvenated asphalt and different aggregates, the rank of adhesion and water resistance from strong to weak is asphalt-limestone＞asphalt- granite, and the rank of the gray entropy correlation between six indices and moisture damage resistance from strong to weak is adhesion work＞spalling work＞VV＞rejuvenator content＞RAP content＞freeze-thaw cycles. Finally, the accuracy of the neural network predicting the moisture damage resistance of rejuvenated asphalt mix reaches 96.188%, which provides a new method to predict the moisture damage resistance of rejuvenated asphalt mixture.

Mechanism Study of Differential Permeability Evolution and Microscopic Pore Characteristics of Soft Clay under Saturated Seepage: A Case Study in Chongming East Shoal

Artificial reclamation is one of the main means of land expansion in coastal cities. However, the permeability of underlying soft clay (USC), derived from the dredged load, has not been paid enough attention, although it is closely related to the long-term deformation and stability of foundation soil. Hence, this paper analyzes the relationship between permeability characteristics and microscopic pore characteristics of USC in Chongming East Shoal (CES), a typical multi-phase reclamation area, through a variable head permeability test, mercury intrusion porosimetry (MIP) test, and scanning electron microscope (SEM) test. Furthermore, grey relation entropy and Pearson correlation analysis are implemented to analyze the influence of micropore parameters on permeability. The results revealed that the seepage process of clay showed a transition from unstable seepage to relatively stable seepage. Meanwhile, the permeability coefficient (PC) attenuated with time cyclically, indicating the alternating effect of the closed and opened unstable seepage channels. During seepage, clay particles could be entrained by pore water and intercepted by pores, thus clogging seepage channels. Then, the increased pore water pressure could break through new seepage channels. The degree of pore clogging was positively correlated with the average cycle period of PCs, and this was also present in the relatively stable stage of PCs. A lower mesopores content, higher fractal dimension, and aggregated flocculate microstructure could promote the clogging effect and result in lower permeability efficiency. Affected by unstable seepage channels, soft clay may face long-term potential deformation in the future, which needs further investigation.

Feature and mechanism analysis of dispersive soil disintegration impacted by soil water content, density, and salinity

AbstractDispersive soil has caused innumerable water‐induced erosion failures of earthen structures in arid regions up to now, among which disintegration, as the first response process, is commonly deemed as the primary inducement but with inadequate understanding. In this study, the disintegration characteristics of a compacted dispersive lean clay with sand were investigated by carrying out laboratory disintegration tests under a water immersion regime. Soil mass water content (ω), dry density (ρd) and total soluble salt content (η) were considered. Results suggest that for dispersive soil, (1) the disintegration process exhibited two distinct modes, which was divided by the ω near the optimum water content; (2) higher ρd delayed disintegration monotonously; (3) increasing η first weakened and then enhanced the disintegration, in which pattern the η at the inflection point increased with increasing ρd, showing a density dependence. Evolutions of representative soil morphology were illustrated. More importantly, the underlying influential mechanism of ω and η to disintegration were elaborated emphatically: (1) the initial clay dispersion level, soil consistency change, and conceptual “constraint force” exerted by soil matric suction jointly determine the disintegration modes; (2) increasing η makes the soil pore solution concentration higher and microstructure simpler, competition between the two leads to nonmonotonic change patterns of disintegration completion time (Td) and defined velocity (Vd); the interactive effect of ρd and η manifests that η produces an additional influence on the base of microstructure created by ρd. Finally, the grey relation entropy analysis was introduced to evaluate the contributions of the three test variables to Td and Vd. The obtained results and proposed perspectives are expected to be conducive to a deeper comprehension of the same or relevant behaviours of dispersive soils in the presence of water, so as to provide new insights for the targeted prevention and control of dispersive soil catastrophes.Highlights Disintegration of dispersive soil shows two distinct water content‐dependent modes. Soil salinity has a two phase impact on disintegration of dispersive soil. Dry density and soil salinity interact affecting disintegration. Relationship between soil dispersion and disintegration is elaborated.

Computed Tomography-Based Texture Analysis as a Predictor of Survival in Patients with T-Cell Lymphomas

Background: T-cell lymphomas constitute a heterogeneous group of hematological malignancies with global poor outcomes. Computed tomography (CT)-based texture analysis (CTTA) is a promising technique to predict the survival of these patients. Objectives: The present study aimed to investigate whether CTTA features on the pretreatment unenhanced CT scans of 18F-fluorodeoxyglucose positron emission tomography/CT (18F-FDG PET/CT) examination can predict the survival of patients with T-cell lymphomas. Patients and Methods: In this retrospective cohort study, patients with T-cell lymphomas, undergoing pretreatment 18F-FDG PET/CT scan during 2008 - 2019, were included, and their clinical and biological characteristics were collected. The mean gray value, entropy, kurtosis, skewness, and standard deviation were derived from the pixel distribution histogram before and after spatial filtration at different anatomic scales in up to five lesions per patient, indicating a high focal uptake on 18F-FDG PET scan. A Lasso-penalized Cox regression analysis was performed to identify independent predictors of overall survival (OS), progression-free survival at 24 months (PFS24), and PFS. Results: A total of 23 patients (7 females and 16 males; median age, 69 years; age range, 33 - 86 years) were included in this study. The CTTA was performed for 60 lesions. The median OS and PFS were 391 days (range, 10 - 3,463 days) and 268 days (range, 10 - 2,321 days), respectively. No CT texture parameter was associated with PFS or PFS24. The standard deviation at a coarse filter scale was independently associated with a poor OS (hazard ratio [HR] = 1.009, confidence interval [CI]: 1.0012 - 1.016, P = 0.02). A value above 143 was associated with a poor prognosis with a specificity of 81%. Conclusion: The pretreatment CTTA-derived tumor standard deviation at a coarse filter scale may be a predictive biomarker of OS in patients with T-cell lymphomas.

Stage-aging characteristics and stages division of crumb rubber modified asphalt binder

Currently, the aged crumb rubber-modified asphalt binder (CRMA) pavements have recycling demands; however, the understanding of the aging behavior of CRMA remains limited. Furthermore, few studies have been conducted to divide the aging stage of CRMA, which is an essential basis for the study of recycling. To solve the above problems, this study aims to analyze the stage-aging characteristics and divide the aging stages of the CRMA to understand better the aging and recycling mechanism of CRMA. The evolution characteristics of the rheological performance of aged CRMA were assessed by high-temperature performance indicators. In addition, thermal gravimetric analysis (TGA) is employed to investigate the degradation degree of crumb rubber modifier (CRM). Finally, the rheological-performance results are combined with the TGA results to divide the aging stages. The results demonstrate that the CRM in CRMA degrades in aging, which shows an initial rapid degradation, then slows down. The process of CRM degradation is accompanied by changes in CRM composition; the natural rubber content of CRM decreases the most significantly, followed by synthetic rubber and filler. The evolution of the properties of aged CRMA is characterized by stages due to CRM degradation, and the CRMA is divided into three aging stages. In addition, the gray correlation entropy analysis demonstrates that the MSCR test is more sensitive to the degradation of CRM in CRMA; it can be used to characterize the stage-aging process of CRMA. In summary, this study's results might fill a significant gap in understanding the aging mechanism of CRMA and provide the basis for recycling the aged CRMA.

Determination of compressive strength of nano modified concrete based on grey entropy correlation method

Determination of compressive strength of nano modified concrete based on grey entropy correlation method

Integrated grey entropy and COPRAS methods for machine selection decision problem

Integrated grey entropy and COPRAS methods for machine selection decision problem

Determination of compressive strength of nano modified concrete based on grey entropy correlation method

Determination of compressive strength of nano modified concrete based on grey entropy correlation method

Development of facile image processing techniques regarding crevice corrosion of U75V high-speed rail steel

In-situ crevice corrosion images of U75V high-speed rail steel samples before and after heat treatment for microstructure refinement were obtained by a self-developed monitoring device, and facile image processing techniques have been developed. Gray value and entropy have been demonstrated to be the significant parameters able to describe the process of crevice corrosion. Gray value has been found to have good correlation with corrosion depth, and distribution of column average gray value can be applied to obtain corrosion depth profiles along crevice depth. Gray histogram is a good indicator to distinguish local preferential dissolution and uniform dissolution via deviation from original peak position and valley height. Entropy means uncertainty of how corrosion patterns develop. Its increase indicates high activity for change of corrosion patterns, while low activity leads to cease of increase. When metal surface has been corroded extensively, entropy will decrease, indicating less potential routes for development of corrosion patterns. This work has provided new ideas on the application of image processing on corrosion study.

Relationship Assessment of COVID-19, Air Pollution, and Copper Demand from the Perspective of Copper Price

Copper in the international market has been priced by copper futures contracts from the London Metal Exchange (LME) and the New York Commodity Exchange (COMEX). Copper prices initially showed a downward trend until March 2020, but after the outbreak of COVID-19, they continued to rise and reached a record high in May 2021. The rise in copper demand also stimulated the continuous growth of copper production. However, a significant amount of smelting flue gas is produced in the copper smelting process. The main component of the flue gas is SO2 and other acid gases, which pollute the environmental atmosphere. At the same time, due to the Chinese government’s effective control of the pandemic, China’s economy continued to grow. Therefore, as one of the world’s largest copper consumers and producers, China’s futures market has attracted attention for its influence on copper pricing and the pollution caused by copper smelting. In this paper, we used the grey entropy method to compare the influence of copper prices on the three futures markets and changes in China’s air pollution in recent years. Our results show that before the pandemic, the influence of the LME futures copper price was the same as the COMEX but greater than the Shanghai Futures Exchange (SHFE). After the outbreak of the pandemic, the influence of the SHFE copper futures price significantly improved and slightly exceeded the LME and COMEX. This result echoes our finding that SO2 has caused serious air pollution in recent years.