Grey Relational Entropy Research Articles

Multiscale groundwater level forecasts with multi-model ensemble approaches: Combining machine learning models using decision theories and bayesian model averaging

Creating precise groundwater level (GWL) prediction models is of crucial significance for the productive use, extended planning, and controlling of limited sub-surface water supplies. In this research, the accuracy of GWL forecasts in Bangladesh was enhanced for three weeks by utilizing ensembles of Machine Learning (ML) models. Six advanced ML-based models were developed and assessed using eight performance indices, and an Overall Ranking (OR) was provided by combining the rankings produced by Grey Relational Analysis (GRA), Variation Coefficient (COV), and Shannon's Entropy (SE). The standalone forecasting models demonstrated excellent performance across the three forecasting horizons, with accuracy values ranging from 0.986 to 0.997 for one-step, 0.971 to 0.999 for two-step, and 0.960 to 0.997 for three-step forecasts at GT3330001. Results also revealed that three ranking techniques (SE, COV, and GRA), as well as their combined ranking (OR), produced different best-performing models at different prediction horizons for different observation wells. Weighted average ensembles of the prediction models were developed by calculating individual model weights using four ensemble modelling techniques: SE, COV, GRA, and Bayesian Model Averaging (BMA). The BMA-based ensemble technique outperformed three benchmark ensemble approaches, achieving R = 0.947, KGE = 0.925, IOA = 0.972, MAE = 0.062 m, and RMSE = 0.123 m for one-step-ahead forecasts at GT3330001. The findings exhibit a consistent trend across other forecasting horizons and observation wells. Finally, the Dempster-Shafer evidence theory was employed to rank the single and composite models. The ranking results demonstrated that the BMA-based ensemble consistently secured the top position (with the weight values of 0.997, 0.991, and 0.987 for one-week, two-weeks, and three-weeks forward forecasts at GT3330001) for all forecasting horizons and observation wells. This study shows that the BMA-based composite model can produce more accurate GWL projections at Bangladesh study location, with potential for application in other regions worldwide.

The Nearshore Marine of ShenZhen Environmental Risk Assessment Method Based on the DPSIR Framework

The nearshore marine areas are the most intensely concentrated regions for human economic activities and serve as vital carriers for the development of the marine economy. Accurately assessing the environmental risks in these areas is of significant importance for the sustainable development of the marine economy. This study constructs an environmental risk assessment system for the nearshore marine areas of Shenzhen City based on the DPSIR framework and evaluates it using the comprehensive index method. Specifically, the study begins by selecting 27 indicators related to the marine environment to construct the evaluation index system. It employs the grey relational analysis and entropy weight method to weight the indicators and finally assesses the environmental risks of Shenzhen's nearshore marine areas from 2013 to 2020 using the comprehensive index method. The study finds that the environmental risks of Shenzhen's nearshore marine areas from 2013 to 2020 are generally low, with the risk score increasing from 0.3277 to 0.7308 year by year, shifting from a more dangerous to a safe risk level. The research indicates that the marine environment of the nearshore areas in Shenzhen is greatly influenced by local human economic activities and the industrial structure of Shenzhen. The study suggests that the environmental safety level of Shenzhen's nearshore marine areas could be improved by leveraging policy guidance, optimizing the industrial structure, and perfecting tourism management methods.

Gray Correlation Entropy-Based Influential Nodes Identification and Destruction Resistance of Rail-Water Intermodal Coal Transportation Network

Evaluating the importance of nodes in coal transportation networks and identifying influential nodes is a crucial study in the field of network science, vital for ensuring the stable operation of such complex networks. However, most existing studies focus on the performance analysis of single-medium networks, lacking research on combined transportation, which is not applicable to China’s coal transportation model. To address this issue, this paper first establishes a static topological structure of China’s coal-iron-water combined transportation network based on complex network theory, constructing a node importance evaluation index system through four centrality indicators. Subsequently, an enhanced TOPSIS method (GRE-TOPSIS) is proposed based on the Grey Relational Entropy Weight (GRE) to identify key nodes in the complex network from local and positional information dimensions. Compared to previous studies, this research emphasizes composite networks, breaking through the limitations of single-medium network research, and combines gray relational analysis with entropy weighting, enhancing the objectivity of the TOPSIS method. In the simulation section of this paper, we establish the model of China’s coal-iron-water combined transportation network and use the algorithm to comprehensively rank and identify key nodes in 84 nodes, verifying its performance. Network efficiency and three other parameters are used as measures of network performance. Through simulated deliberate and random attacks on the network, the changing trends in network performance are analyzed. The results show that in random attacks, the performance drops to around 50% after damaging nearly 40 ordinary nodes. In contrast, targeting close to 16 key nodes in deliberate attacks achieves a similar effect. Once key nodes are well protected, the network exhibits a certain resistance to damage.

Investigation on cracking resistance mechanism of basalt-polypropylene fiber reinforced concrete based on SEM test

In order to study the anti-crack mechanism of basalt-polypropylene fiber reinforced concrete (BPFRC), based on the restrained shrinkage test of BPFRC, the anti-crack enhancement mechanism of basalt fiber and polypropylene fiber was discussed through SEM microscopic test, and the sensitivity index of BPFRC's anti-crack performance was studied by combining grey relational theory and entropy weight method. The results show that basalt fiber has a significant inhibitory effect on the initiation and propagation of micro-cracks, and polypropylene fiber has a more obvious inhibitory effect on the propagation of macro-cracks. Mixing basalt fiber and polypropylene fiber into concrete can improve the pore structure of concrete matrix, reduce the initial defects of concrete matrix, enhance the density of the interface transition zone between aggregate and matrix, make concrete play a bridging role in different stages of stress deformation, and enhance the crack resistance of concrete more significantly. Grey relational theory combined with entropy weight method shows that the splitting tensile strength has the most significant influence on the crack resistance of BPFRC. This study can provide a new method for the sensitivity index analysis and crack resistance evaluation of concrete.

Modeling and Optimization of Mechanical Cutting of Downhole Tubing

Summary Mechanical cutting of tubing plays a vital role in solving the problem of pipe string jams in workover operations of oil wells. To improve the efficiency of downhole cutting operations and save operation costs, it is necessary to optimize the parameters of downhole-cutting operations. However, previous research did not involve related engineering problems. Therefore, in this paper, the equivalent simulation experiment of downhole cutting is conducted based on actual field data. Cutting speed, feed rate, and cutting thickness are used as parameters while cutting power (P), material removal rate (MRR), and tool chip temperature (T) are used as optimization objectives with the trade-offs between the three objectives considered. The full factorial design is used to carry out the experiments and the combination of grey relational analysis (GRA) method and entropy weight method is used to determine the weight of the three objectives. The influence of cutting parameters on the optimization objectives is analyzed, the mathematical model between cutting parameters and a single objective is established, and the adaptive weight particle swarm algorithm is used to optimize the coefficients of this model. The relationship between the multiobjective model and cutting parameters is established using a multiple nonlinear regression model, and the selection of interaction terms is completed using a stepwise regression method. The reliability of the model is also verified. This paper provides a reference for future research on downhole-cutting problems.

Study on the substance basis of the efficacy of eucommiae cortex before and after salt processing for the treatment of kidney-yang deficiency syndrome based on the spectrum-effect relationship

Ethnopharmacological relevanceKidney-Yang deficiency syndrome (KYDS) is one of the common diseases of the elderly and closely related to the ageing of the body, it has a major impact on the quality of life of the patient. Eucommiae Cortex (EC) is the dried bark of Eucommia ulmoides Oliv. Which has the effect of tonifying the liver and kidneys, strengthening the muscles and bones. In Traditional Chinese Medicine clinics, EC is commonly used in the treatment of KYDS, but the material basis for the improvement of its efficacy in treating KYDS after salt processing remains unclear. Aim of the studyThis study aimed to find the main active ingredients that could improve the treatment of KYDS efficacy of EC after salt processing. Materials and methodsFirstly, the fingerprints of raw and salt-processed EC were established to determine the common components by using HPLC, and then an experimental study on the treatment of KYDS efficacy was carried out to compare the difference in the efficacy between raw and salt-processed EC. Thirdly, the spectrum-effect relationship of chemical components and pharmacodynamic indexes was established by using Grey Relational Analysis and Entropy Method. Finally, the network pharmacology and molecular docking technique was used to verify the kidney tonifying effect of the active ingredients of EC. ResultsAccording to the results of the analysis of hormonal index levels on the hypothalamic-pituitary-target gland axis and the extent of renal lesions, the therapeutic effect of EC on KYDS was mainly reflected in the regulation of the Adrenocorticotropic hormone, Corticosterone in the hypothalamic-pituitary-adrenal axis and Tri-iodothyronine, Tetra-iodothyronine in the hypothalamic-pituitary-thyroid axis, moreover the therapeutic effect of salt-processed EC was stronger than that of raw EC. The pharmacologically active ingredients that improved its treatment of KYDS efficacy after salt processing were peak 1 (geniposidic acid), peak 2 (chlorogenic acid), peak 5 (geniposide), peak 6 (genipin), peak 7 (pinoresinol diglucoside) and peak 11 (hyperoside). Meanwhile, the results of network pharmacology and molecular docking showed that the 6 active ingredients could exert kidney tonic effects through multiple signaling pathways by acting on core targets such as AKT1 and PTGS2. ConclusionAs far as we known, this was the first time to establish and compare the spectrum-effect relationship between raw and salt-processed EC, which laid the foundation for the pharmacokinetics studies of EC and provided a reference for future EC studies.

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.

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.

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.

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.

Effect of concrete composition on drying shrinkage behavior of ultra-high performance concrete

The concrete compositions have great effects on the drying shrinkage behavior of ultra-high performance concrete (UHPC). Five factors including water-to-binder ratio (w/b) and contents of steel fiber, superplasticizer, silica fume and fly ash were considered to evaluate their influences on the drying shrinkage behaviors of UHPC in this investigation. Based on the drying shrinkage test results, the effect degrees of these factors were analyzed by the gray relation entropy analysis. Then the microstructure and pore distributions of UHPC samples were measured by scanning electron microscope and mercury intrusion porosimetry for mechanism analyses. The results reveal that a lower w/b or higher content of fly ash is conducive to achieving a reduction in drying shrinkage of UHPC, while the additions of superplasticizer and silica fume have an adverse effect on drying shrinkage, resulting in increased drying shrinkage, and the effect of steel fiber on drying shrinkage is not monotonic, its optimum dosage is 50 kg/m3 in this work and a lower or higher amount will cause an increased DSS of UHPC compared with the one with an optimum dosage. The five factors can affect the drying shrinkage behavior of UHPC by principally changing the microtopography and internal pore structure of the concrete matrix, according to the gray relation entropy analysis, the effect degrees of studied factors on drying shrinkage of UHPC are as follows: w/b > superplasticizer > silica fume > fly ash > steel fiber.

Grey model study on strength and pore structure of self-compacting concrete with different aggregates based on NMR

To promote the application of machine-made sand and shale ceramsite in self-compacting concrete (SCC), this paper takes four kinds of SCC with different aggregates as the research object. The working performance and mechanical properties of four kinds of SCC are tested when gravel and shale ceramsite are used as coarse aggregate and machine-made sand and river sand are used as fine aggregates. The T2 spectrum of self-compacting concrete with different aggregates at different ages is obtained by NMR technology, and the pore size distribution curve is obtained. Then, the grey relation entropy theory is used to analyze the influence of pore structure on the mechanical properties of SCC. Finally, based on the pore structure parameters, a GM (1,3) prediction model for the compressive strength of SCC is established. The results show that: shale ceramsite and machine-made sand can be used as substitutes for gravel and river sand; The working performance of shale ceramsite SCC and river sand SCC is better than that of gravel SCC and machine-made sand SCC; The mechanical properties of gravel SCC and machine-made sand SCC are better than shale ceramsite SCC and river sand SCC, respectively. Small pores and porosity less than 0.02 μm have little effect on the mechanical properties of SCC, while spectral area and larger pores have a greater impact on it; GM（1,3）model can achieve a more accurate prediction of the mechanical properties of shale ceramsite concrete, and the prediction error of gravel concrete is relatively large, reflecting that compared with shale ceramsite, gravel has a great influence on the mechanical properties of concrete.

Adaptive approximation-based multi-objective hybrid optimization method for dual-gradient top-hat structures

In this article, an adaptive approximation-based multi-objective hybrid optimization method, integrating a multi-objective decision-making method, adaptive approximation method and hybrid optimization method, is developed. In particular, a multi-objective decision-making method developed by combining a weight strategy inspired by grey relational analysis and entropy analysis is applied to normalize multiple objectives; the trust region is introduced into the support vector regression model to solve the problem of the sequential sampling for the approximation model; a hybrid optimization algorithm combining the genetic algorithm pattern search algorithm is developed to further assist the surrogate model-based optimization. Finally, a novel dual-gradient structure with graded thickness and graded material property along the axial direction is applied to the crashworthiness optimization design. The results demonstrate that the developed hybrid method has faster optimization efficiency than the Pointer algorithm built into Isight commercial software, and the final optimized structure is superior to the original one.

Weighting analysis on air pollution among recent years in China via grey theory models

The priority of national development has always been economic development during the recent decades in China, so a lot of energy consumption was needed to support rapid economic development, accompanied by a number of different air pollution emissions, including SO2, NO2 CO, and PM2.5. Based on awareness of environmental protection and sustainable energy development, researchers aimed to propose strategies to reduce the amount of air pollution generation in China derived from intense industrialization. The calculation of the correlation coefficient showed high values, so the correlation of air pollutants is highly related. This study aimed to realize the outcome of the implementation of air pollution reduction acts. Therefore, the grey relational grade and grey entropy were used to analyze the air pollution trend from 2013 to 2020 due to the specific function of the grey theory. The results of this study showed that the curves of SO2, PM2.5, and CO showed a clear decreasing trend. Furthermore, the SO2 curve still decreased in the periods of 2018–2020. The most important index for air pollutants is SO2 after the calculation of grey entropy, which corresponds to the fact that the coal resource is the main energy source in the fossil fuel industries for economic growth. However, the effects of these implementations regarding air pollution reduction sufficiently control air pollution emission, especially SO2 emission.

The influencing factors of evaporation residue of emulsified modified asphalt to optimize the environmental adaptability

Compared with traditional asphalt, emulsified asphalt occurs to be a better low-temperature usability and environmental adaptability, which can reduce environmental pollution and energy consuming during road construction. The low-temperature ductility is a very important indicator to evaluate the environmental adaptability of emulsified asphalt. However, the relevance between microstructure and low-temperature ductility of modified asphalt is still rarely reported. Herein, we reported the first successful unfolding of the microscopic mechanism of ductility attenuation of the modified emulsified asphalt by combining experiments and characterization: Emulsifiers and additives had greater influence on the low-temperature ductility. Anionic and cationic emulsifiers had the similar ductility loss. Adding a non-ionic emulsifier OP-10 could be a solution to improve the ductility. The effect of the temperature change occurred less significant compared to the pH evolution of surfactant solution. The grey relation entropy (GRE) analysis revealed that the emulsifier structure (C/H ratio) would be the most important factor to affect the low-temperature ductility. The macro, micro and nano scales of modified emulsified asphalt were correlated, revealing in-depth that the aggregation and inter-chains interaction of styrene-butadiene-styrene (SBS) were the internal mechanism leading to the ductility loss. The change of glass transition temperature (Tg) was proposed to correlate the microstructural factor with the ductility. Moreover, the combination of ductility test and bending beam rheometer (BBR) test could be an effective way to evaluate the low-temperature performance of asphalt.

Comparative analysis of anti-osteoporosis efficacy in Radix Dipsaci before and after processing with salt based on spectrum-effect relationship

Radix Dipsaci (RD) is the dry root of the Dipsacus asper Wall. ex DC., which has the effect of strengthening muscles and bones. The purpose of this study was to find the main active ingredients that could improve the anti-osteoporosis efficacy of RD after processing with salt. The fingerprints of raw and salt-processed RD were established by HPLC-DAD to determine the common components. Then, an experimental study on the anti-osteoporosis efficacy was carried out to compared the difference in the efficacy between raw and salt-processed RD. Pharmacological results showed that, compared with the model group, both the raw and salt-processed RD were able to increase the Ca, bone mineral content, bone mineral density, trabeculae bone area and number of trabeculae bone of rats, and reduce the P, alkaline phosphatase, osteocalcin and trabecular bone separation of rats. Under the same dose, the pharmacological effect of salt-processed RD group was better than that of raw RD group. Finally, spectrum-effect relationship between fingerprints and anti-osteoporosis efficacy of RD was assessed by grey relational analysis and entropy method to screening out the ingredients that affect the anti-osteoporosis efficacy in RD after processing with salt. The results showed that the anti-osteoporosis efficacy of salt-processed RD was stronger than that of raw RD, and the pharmacologically active ingredients that improved its anti-osteoporosis efficacy after processing with salt were peak 4, peak 7 (caffeic acid), peak 8 (loganin), peak 12 (isochlorogenic acid C), peak 13 (dipsanoside A) and peak 14. As far as we known, this was the first time to establish the spectrum-effect relationship between RD and anti-osteoporosis efficacy, which laid the foundation for the follow-up research on the pharmacodynamic components and molecular mechanism of RD.

Land Comprehensive Carrying Capacity of Major Grain-Producing Areas in Northeast China: Spatial–Temporal Evolution, Obstacle Factors and Regulatory Policies

Major grain-producing areas in Northeast China serve as a significant national commodity in their role as grain bases. In order to achieve sustainable land use in such areas and ensure national food security, it is critical to understand the spatial–temporal evolution features of the land comprehensive carrying capacity of such areas, ascertain major obstacle factors and propose regulatory policies for effectively improving the land comprehensive carrying capacity. In this paper, a TOPSIS model based on grey relational entropy weight is developed to analyze the spatial–temporal evolution features of the land comprehensive carrying capacity of major grain-producing areas in Northeast China from 2000 to 2020, and an obstacle degree model is employed to determine the main obstacles to improving the land comprehensive carrying capacity of major grain-producing areas in Northeast China. The study results show the following: (1) The land comprehensive carrying capacity of major grain-producing areas in Northeast China is at a low level, showing an N-shaped trendline, and its spatial–temporal evolution features are subject to changes in land food carrying capacity, land economic carrying capacity and land ecological carrying capacity.(2) The main obstacle factors for improving the land comprehensive carrying capacity of major grain-producing areas in Northeast China are urbanization rate, gross industrial output per hectare and industrial solid waste emission per hectare. Cultivated land area per capita, grain output per hectare and industrial wastewater discharge per hectare have recently become obstacle factors for the land comprehensive carrying capacity of the study areas. Based on these results, the paper proposes regulatory strategies for stabilizing agricultural population transfer to avoid its reversal, exploring the optimization and upgrading of secondary sector structures to promote a low-carbon transition to green industries, and implementing cultivated land protection policies to steadily boost cultivated land grain productivity, with a view to increasing the land comprehensive carrying capacity of major grain-producing areas in Northeast China. The findings of this study act as a scientific reference for enhancing the land comprehensive carrying capacity of major grain-producing areas in Northeast China, which is crucial for ensuring national food security.

Risk assessment and implementation of deformation disaster for operation tunnel based on entropy weight-grey relational analysis

Prevention is of paramount importance in tunnel engineering, especially in operation tunnel. In this study, the deformation data of Suzhou Metro Line 1 are used to evaluate the health of shield tunnel during operation. Firstly, the relationship between effective ratio of bending rigidity and tunnel deformation is analyzed, the results show that the effective ratio of bending rigidity has a negative power relationship with the tunnel deformation, and the conversion from deformation data to effective ratio of bending rigidity is realized and the corresponding risk classification criterion are established. Secondly, Grey Relational Analysis and Entropy Weight Method are used to deal with the deformation data, which overcomes the problem that data selection is not representative. Finally, the optimum effective ratio of bending rigidity is obtained successfully to complete the risk assessment of operation tunnel, and the assessment result is highly consistent with actual project. In addition, the corresponding application named Operation Tunnel Deformation Risk Assessment System is developed by using computer technology, which saves time for assessment and increases flexibility. The risk assessment method passes validation in the case tunnel, which can provide a reference for the disaster prevention in operation tunnel.