Using a grey relational analysis in an improved Grunow-Finke assessment tool to detect unnatural epidemics.

The Grunow-Finke epidemiological assessment tool (GFT) has several limitations in its ability to differentiate between natural and man-made epidemics. Our study aimed to improve the GFT and analyze historical epidemics to validate the model. Using a gray relational analysis (GRA), we improved the GFT by revising the existing standards and adding five new standards. We then removed the artificial weights and final decision threshold. Finally, by using typically unnatural epidemic events as references, we used the GRA to calculate the unnatural probability and obtain assessment results. Using the advanced tool, we conducted retrospective and case analyses to test its performance. In the validation set of 13 historical epidemics, unnatural and natural epidemics were divided into two categories near the unnatural probability of 45%, showing evident differences (p < 0.01) and an assessment accuracy close to 100%. The unnatural probabilities of the Ebola virus disease of 2013 and Middle East Respiratory Syndrome of 2012 were 30.6% and 36.1%, respectively. Our advanced epidemic assessment tool improved the accuracy of the original GFT from approximately 55% to approximately 100% and reduced the impact of human factors on these outcomes effectively.

Estimation of Knee Extension Force Using Mechanomyography Signals Based on GRA and ICS-SVR.

During lower-extremity rehabilitation training, muscle activity status needs to be monitored in real time to adjust the assisted force appropriately, but it is a challenging task to obtain muscle force noninvasively. Mechanomyography (MMG) signals offer unparalleled advantages over sEMG, reflecting the intention of human movement while being noninvasive. Therefore, in this paper, based on MMG, a combined scheme of gray relational analysis (GRA) and support vector regression optimized by an improved cuckoo search algorithm (ICS-SVR) is proposed to estimate the knee joint extension force. Firstly, the features reflecting muscle activity comprehensively, such as time-domain features, frequency-domain features, time-frequency-domain features, and nonlinear dynamics features, were extracted from MMG signals, and the relational degree was calculated using the GRA method to obtain the correlation features with high relatedness to the knee joint extension force sequence. Then, a combination of correlated features with high relational degree was input into the designed ICS-SVR model for muscle force estimation. The experimental results show that the evaluation indices of the knee joint extension force estimation obtained by the combined scheme of GRA and ICS-SVR were superior to other regression models and could estimate the muscle force with higher estimation accuracy. It is further demonstrated that the proposed scheme can meet the need of muscle force estimation required for rehabilitation devices, powered prostheses, etc.

[Simultaneous determination of multiple bioactive constituents in Abelmoschi Corolla by UFLC-QTRAP-MS/MS].

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 38 active components in Abelmoschi Corolla, including flavonoids, organic acids, nucleosides and amino acids, so as to investigate the effects of different harvesting and processing methods on multi-active components in Abelmoschi Corolla. The chromatographic separation was performed on a XBridg®C_(18) column(4.6 mm×100 mm, 3.5 µm) with(0.1% formic acid water) methanol-acetonitrile(1∶1) as the mobile phase for gradient elution at 30 ℃. The flow rate was 0.5 mL·min~(-1). The components were detected in a multiple-reaction monitoring(MRM) mode. The gray relational analysis(GRA) was used to comprehensively evaluate the multiple active components of Abelmoschi Corolla at different harvesting times and drying temperatures. The results showed that 38 components had a good linearity with correlation coefficients all above 0.999 0. The method featured a good precision, repeatability and stability with the relative stan-dard deviations(RSDs) of less than 5.0%. Recoveries ranged from 98.06% to 104.4% with RSD between 0.22% and 4.9%. The results of GRA indicated that a better quality in the samples collected on September 9 th. Samples dried at 90 ℃ had a better quality. The established method is accurate and reliable, and can be used to assess the internal quality of Abelmoschi Corolla. This study can provide basic materials for determining appropriate harvesting time and processing method of Abelmoschi Corolla.

An approach for assessing ecosystem-based adaptation in coral reefs at relatively high latitudes to climate change and human pressure.

Relatively high-latitude waters are supposed as a refuge for corals under ocean warming. A systematic assessment of the Weizhou Island reef in the northern South China Sea, a relatively high-latitude region, shows that the ecosystem restoration index decreased from 0.96 to 0.62 during the period between 1990 and 2015. Although the biotic community, supporting services, and regulating services remained at good or very good states, the provisioning services, cultural services, and especially habitat structure deteriorated to very poor or moderate states. Gray relational analysis showed that these ecological declines exhibited a strong relationship with human pressures from tourism activities and the petrochemical industry. The recoveries of the biotic community and supporting services that benefited from wintertime warming appeared to be partly offset by intensive human pressures. The long-term effects on ecosystem structure and functions suggest that anthropogenic disturbances have impaired the possibility of this area serving as a potential thermal refuge for reef-building corals in the South China Sea. This study thus provides an integrated approach for assessing the adaptive responses of coral reef ecosystems to climate change and local human activities.

[Analysis and evaluation of dynamic accumulation of multiple bioactive constituents in Spatholobi Caulis].

A method was established for simultaneous determination of 21 active constituents including flavanols, isoflavones, flavonols, dihydroflavones, dihydroflavonols, chalcones, pterocarpan, anthocyanidins and phenolic acids in Spatholobi Caulis by ultra fast liquid chromatography with triple quadrupole linear ion trap mass spectrometry(UFLC-QTRAP-MS/MS). Then, it was employed to analyze and evaluate the dynamic accumulation of multiple bioactive constituents in Spatholobi Caulis. The chromatographic separation was performed on a XBridge®C_(18)(4.6 mm×100 mm, 3.5 µm) at 30 ℃ with a gradient elution of 0.3% formic acid aqueous solution-methanol, and the flow rate was 0.8 mL·min~(-1), using multiple-reaction monitoring(MRM) mode. A comprehensive evaluation of the multiple bioactive constituents was carried out by gray correlation analysis(GRA). The 21 target components showed good linearity(r>0.999 0) in the range of the tested concentrations. The average recovery rates of the 21 components were from 97.46% to 103.6% with relative standard deviations less than 5.0%. There were differences in the contents of 21 components in Spatholobi Caulis at diffe-rent harvest periods. Spatholobi Caulis had high quality from early November to early December, which is consistent with the local tradi-tional harvest period. This study reveals the rule of the dynamic accumulation of 21 components in Spatholobi Caulis and provides basic information for the suitable harvest time. At the same time, it provides a new method reference for the comprehensive evaluation of the internal quality of Spatholobi Caulis.

Quality evaluation of Eucommiae Cortex processed by different methods and "sweating" conditions based on simultaneous determination of multiple bioactive constituents combined with gray relational analysis.

Eucommiae Cortex is a classical traditional Chinese medicine, which needs to be processed by "sweating" methods. To select the suitable processing method and "sweating" processing condition for Eucommiae Cortex, in this study, the quality of Eucommiae Cortex was evaluated based on simultaneous determination of multiple bioactive constituents combined with gray relational analysis. The contents of lignans, iridoids, penylpropanoids, flavonoids, and phenols in samples were simultaneously determined using ultra-fast performance liquid chromatography coupled with triple quadrupole-linear ion trap tandem mass spectrometry. The chromatographic separation was performed on a Synergiۛ Hydro-RP 100 Å column (100 mm × 2.0 mm, 2.5 µm) at 30°C with a gradient elution of acetonitrile with 0.1% formic acid/0.1% aqueous formic acid as the mobile phase. Furthermore, gray relational analysis was performed to evaluate and sort the samples according to the contents of 14 constituents by calculating the relative correlation degree of each sample. The results demonstrated that the quality of Eucommiae Cortex "sweating" at source area was better and the better "sweating" condition was to scrape off the cork layer before "sweating" with straw covering and sun drying. The developed method could provide the foundation and support for "sweating" processing method of Eucommiae Cortex in normalization and standardization.

Sensitive indicators of Stipa bungeana response to precipitation under ambient and elevated CO2 concentration.

Precipitation is a primary environmental factor in the semiarid grasslands of northern China. With increased concentrations of atmospheric greenhouse gases, precipitation regimes will change, and high-impact weather events may be more common. Currently, many ecophysiological indicators are known to reflect drought conditions, but these indicators vary greatly among species, and few studies focus on the applicability of these drought indicators under high CO2 conditions. In this study, five precipitation levels (- 30%, - 15%, control, + 15%, and + 30%) were used to simulate the effects of precipitation change on 18 ecophysiological characteristics in Stipa bungeana, including leaf area, plant height, leaf nitrogen (N), and chlorophyll content, among others. Two levels of CO2 concentration (ambient, 390 ppm; 550 ppm) were used to simulate the effects of elevated CO2 on these drought indicators. Using gray relational analysis and phenotypic plasticity analysis, we found that total leaf area or leaf number (morphology), leaf water potential or leaf water content (physiology), and aboveground biomass better reflected the water status of S. bungeana under ambient and elevated CO2 than the 13 other analyzed variables. The sensitivity of drought indicators changed under the elevated CO2 condition. By quantifying the relationship between precipitation and the five most sensitive indicators, we found that the thresholds of precipitation decreased under elevated CO2 concentration. These results will be useful for objective monitoring and assessment of the occurrence and development of drought events in S. bungeana grasslands.

Spectrum-Effect Relationships between Fingerprints of Caulophyllum robustum Maxim and Inhabited Pro-Inflammation Cytokine Effects.

Caulophyllum robustum Maxim (CRM) is a Chinese folk medicine with significant effect on treatment of rheumatoid arthritis (RA). This study was designed to explore the spectrum-effect relationships between high-performance liquid chromatography (HPLC) fingerprints and the anti-inflammatory effects of CRM. Seventeen common peaks were detected by fingerprint similarity evaluation software. Among them, 15 peaks were identified by Liquid Chromatography-Mass Spectrometry (LC-MS). Pharmacodynamics experiments were conducted in collagen-induced arthritis (CIA) mice to obtain the anti-inflammatory effects of different batches of CRM with four pro-inflammation cytokines (TNF-α, IL-ß, IL-6, and IL-17) as indicators. These cytokines were suppressed at different levels according to the different batches of CRM treatment. The spectrum-effect relationships between chemical fingerprints and the pro-inflammation effects of CRM were established by multiple linear regression (MLR) and gray relational analysis (GRA). The spectrum-effect relationships revealed that the alkaloids (N-methylcytisine, magnoflorine), saponins (leiyemudanoside C, leiyemudanoside D, leiyemudanoside G, leiyemudanoside B, cauloside H, leonticin D, cauloside G, cauloside D, cauloside B, cauloside C, and cauloside A), sapogenins (oleanolic acid), ß-sitosterols, and unknown compounds (X3, X17) together showed anti-inflammatory efficacy. The results also showed that the correlation between saponins and inflammatory factors was significantly closer than that of alkaloids, and saponins linked with less sugar may have higher inhibition effect on pro-inflammatory cytokines in CIA mice. This work provided a general model of the combination of HPLC and anti-inflammatory effects to study the spectrum-effect relationships of CRM, which can be used to discover the active substance and to control the quality of this treatment.

Mechanical, Dielectric and Flame-Retardant Properties of GF/PP Modified with Different Flame Retardants.

With the rapid development of electronic information technology, higher requirements have been put forward for the dielectric properties and load-bearing capacity of materials. In continuous glass fiber-reinforced thermoplastic composites, polypropylene matrix is a non-polar polymer with a very low dielectric constant and dielectric loss, but polypropylene is extremely flammable which greatly limits its application. Aiming at the better application of flame retardant-modified continuous glass fiber-reinforced polypropylene composites (FR/GF/PP) in the field of electronic communication, the effects of four different kinds of flame retardants (Decabromodiphenyl ethane (DBDPE), halogen-free one-component flame retardant (MONO), halogen-free compound flame retardant (MULTI), and intumescent flame retardant (IFR)) on the properties of FR/GF/PP were compared, including the mechanical properties, dielectric properties and flame-retardant properties. The results showed that among the FR/GF/PP, IFR has the highest performance in mechanical properties, MULTI has better performance in LOI, DBDPE and IFR have better performance in flame retardant rating, and DBDPE and IFR have lower dielectric properties. Finally, gray relational analysis is applied to propose an approach for selecting the optimal combination (flame retardant type and flame-retardant content) of comprehensive performance. In the application exemplified in this paper, the performance of IFR-3-modified GF/PP is optimized.

Study of Synthesis of Dual-Curing Thermoplastic Polyurethane Hot-Melt Adhesive and Optimization by Using Gray Relational Analysis to Apply in Fabric Industry to Solve Seamless Bonding Issues.

People wear clothes for warmth, survival and necessity in modern life, but in the modern era, eco-friendliness, shortened production times, design and intelligence also matter. To determine the relationship between data series and verify the proximity of each data series, a gray relational analysis, or GRA, is applied to textiles, where seamless bonding technology enhances the bond between components. In this study, a polyurethane prepolymer, 2-hydroxyethyl acrylate (2-HEA) as an end-capping agent and n-octyl acrylate (ODA) as a photoinitiator were used to synthesize a dual-curing polyurethane hot-melt adhesive. Taguchi quality engineering and a gray relational analysis were used to discuss the influence of different mole ratios of NCO:OH and the effect of the molar ratio of the addition of octyl decyl acrylate on the mechanical strength. The Fourier transform infrared spectroscopy (FTIR) results showed the termination of the prepolymer's polymerization reaction and the C=O peak intensity at 1730 cm-1, indicating efficient bonding to the main chain. Advanced Polymer Chromatography (APC) was used to investigate the high-molecular-weight (20,000-30,000) polyurethane polymer bonded with octyl decyl acrylate to achieve a photothermosetting effect. The thermogravimetric analysis (TGA) results showed that the thermal decomposition temperature of the polyurethane hot-melt adhesive also increased, and they showed the highest pyrolysis temperature (349.89 °C) for the polyhydric alcohols. Furthermore, high peel strength (1.68 kg/cm) and shear strength (34.94 kg/cm2) values were detected with the dual-cure photothermosetting polyurethane hot-melt adhesive. The signal-to-noise ratio was also used to generate the gray relational degree. It was observed that the best parameter ratio of NCO:OH was 4:1 with five moles of monomer. The Taguchi quality engineering method was used to find the parameters of single-quality optimization, and then the gray relation calculation was used to obtain the parameter combination of multi-quality optimization for thermosetting the polyurethane hot-melt adhesive. The study aims to meet the requirements of seamless bonding in textile factories and optimize experimental parameter design by setting target values that can effectively increase production speed and reduce processing time and costs as well.

Impact of Cryogenic Treatment Process on the Performance of 51CrV4 Steel.

The working load on automotive components is continuously rising, and the mechanical performance requirements for component materials are rising along with the growth trend toward light weight and high dependability in automobiles. In this study, the response characteristics of 51CrV4 spring steel were taken to be its hardness, wear resistance, tensile strength, and impact toughness. Prior to tempering, cryogenic treatment was introduced. Through the Taguchi method and gray relational analysis, the ideal process parameters were discovered. The ideal process variables were the following: a cooling rate of 1 °C/min, a cryogenic temperature of -196 °C, a holding time of 24 h, and a cycle number of three. An analysis of variance revealed that the holding time had the greatest effect on the material properties, with an effect of 49.01%. The yield limit of 51CrV4 was increased by 14.95% and the tensile strength was increased by 15.39% with this group of processes, and the wear mass loss was reduced by 43.32%. The mechanical qualities had a thorough upgrade. Microscopic analysis revealed that cryogenic treatment resulted in refinement of the martensite structure and significant differences in orientation. Additionally, bainite precipitation occurred, exhibiting a fine needle-like distribution, which positively influenced impact toughness. Analysis of the impact fracture surface showed that cryogenic treatment led to an increase in dimple diameter and depth. Further analysis of the elements revealed that calcium (Ca) weakened the negative effect of sulfur (S) on 51CrV4 spring steel. The overall improvement in material properties provides guidance for practical production applications.

Measuring the efficiency of public hospitals: A multistage data envelopment analysis in Fujian Province, China.

Objective: The present study aimed to evaluate the operational efficiency of public hospitals in Fujian Province and the factors responsible for the inefficiency of these hospitals and provide relevant suggestions for health policymakers in allocating service resources. Method: In the first stage of the research, the variables affecting the efficiency of hospitals were extracted by qualitative and quantitative methods, including literature optimization, gray related analysis and gray clustering evaluation. In the second stage, the data envelopment analysis (DEA) method was used to evaluate the operational efficiency of 49 hospitals of different levels and types selected by sampling in 2020. Finally, a Tobit regression model with introduced institutional factors and background factors was established to study the main influencing factors of hospital inefficiency. Results: In the first stage, 10 input variables and 10 output variables necessary from the mangers' point of view were identified to test efficiency. In the second stage, the average comprehensive TE, PTE, and SE of 49 sample hospitals was 0.802, 0.888, and 0.902, respectively. 22.45% of these hospitals met the effective criteria, i.e., the overall effective rate was 22.45%. The low SE value of the hospital was the main reason hindering the improvement of the comprehensive efficiency value. The overall effective rate of secondary public hospitals (30.77%) was higher than that of tertiary public hospitals (19.44%), and the overall effective rate of public specialized hospitals (30%) was higher than that of general public hospitals (18.92%). Based on the third stage results, the bed occupancy rate (BOR) and the proportion of beds (POB) were major factors affecting the operation efficiency of grade III hospitals (p < 0.01). However, the operating efficiency of grade II hospitals was significantly affected by POB and regional per capita GDP(GDPPC) (p < 0.05). Moreover, the impact of BOR and GDPPC was positive, and POB was negatively correlated with hospital operation efficiency. Conclusions: The study results indicated that the overall operation efficiency of public hospitals in Fujian Province is low. This study revealed that intervention should be strengthened from a policy and management perspective to improve the operation efficiency of public hospitals.

Research on Fatigue-Healing Performance of Asphalt Mixture Based on the Semicircular Bending Test.

In order to study the self-healing performance of macroscopic fractures of asphalt mixtures, semicircular bending (SCB) tests were used to test 90# base asphalt mixtures, SBS (Styrene-Butadiene-Styrene) modified asphalt mixtures, and SBS + CR (Chloroprene Rubber) composite modified asphalt mixtures. The F-H-F (the asphalt mixture specimen was fatigued for a certain number of times, then healed under certain conditions, and then fatigued until destroyed) test was carried out, and the fatigue life recovery rate of the fatigue test before and after healing was defined as the healing index (HI). The gray correlation analysis method was used to judge the influence degree of influencing factors on fatigue-healing according to the correlation index. The results show the type of asphalt has the most significant influence on the healing ability of the asphalt mixture. In the case of complete healing, the fatigue-healing performance of the SBS + CR composite modified asphalt mixture was the best, followed by the SBS-modified asphalt mixture, and 90# base asphalt. When the healing temperature is close to the softening point of asphalt, the healing performance of 90# base asphalt is better when the healing temperature is low. When the healing time is longer, the healing performance is better, and there is an optimal healing time. The healing index decreased with the increase in the degree of damage. When the degree of damage is too large, the asphalt mixture will be difficult to heal.

Multi-Objective Optimization of Epoxy Resin Adhesive for Pavement Toughened by Self-Made Toughening Agent.

Epoxy resin adhesive for pavement is often insufficient in flexibility and toughness. Therefore, a new type of toughening agent was prepared to overcome this shortcoming. To achieve the best toughening effect of a self-made toughening agent on an epoxy resin adhesive, its ratio to the epoxy resin needs to be optimally selected. A curing agent, a toughening agent, and an accelerator dosage were chosen as independent variables. The epoxy resin's adhesive tensile strength, elongation at break, flexural strength, and flexural deflection were used as response values to establish a single-objective prediction model of epoxy resin mechanical property indexes. Response surface methodology (RSM) was used to determine the single-objective optimal ratio and analyze the effect of factor interaction on epoxy resin adhesive's performance indexes. Based on principal component analysis (PCA), multi-objective optimization was performed using gray relational analysis (GRA) to construct a second-order regression prediction model between the ratio and gray relational grade (GRG) to determine the optimal ratio and to validate it. The results showed that the multi-objective optimization using response surface methodology and gray relational analysis (RSM-GRA) was more effective than the single-objective optimization model. The optimal ratio of epoxy resin adhesive was 100 parts of epoxy resin, 160.7 parts curing agent, 16.1 parts toughening agent, and 3.0 parts accelerator. The measured tensile strength was 10.75 MPa, elongation at break was 23.54%, the bending strength was 6.16 MPa, and the bending deflection was 7.15 mm. RSM-GRA has excellent accuracy for epoxy resin adhesive ratio optimization and can provide a reference for the epoxy resin system ratio optimization design of complex components.

Research on adaptive combined wind speed prediction for each season based on improved gray relational analysis.

The stability of the power grid and the operational security of the power system depend on the precise prediction of wind speed. In consideration of the nonlinear and non-stationary characteristics of wind speed in different seasons, this paper employs the weight of wind resource index calculated by triangular fuzzy analytic hierarchy process (TF-AHP), criteria importance through inter-criteria correlation (CRITIC), and entropy weight method (EWM) to improve gray correlation analysis (GRA) and obtain the gray correlation degree of each season. In addition, a wind speed prediction model is provided that includes single-layer and two-layer weighting and is based on both deep and shallow machine learning models. At first, we establish each quarter's wind resource characteristics at typical monthly intervals of 10 min, 30 min, 60 min, and 120 min. The GRA's TF-AHP-CRITIC-EWM, enhanced with subjective and objective weights, is used to assess the available wind resources in each season and to compute the forecasted combination of wind speed for each season. As the final prediction results, the prediction values of each layer model are evaluated independently. For the intervals with considerable errors, we apply wavelet denoising and replacement combination. The simulation findings show that the proposed combined model surpasses earlier benchmark models in terms of goodness of fit, prediction accuracy, and generalizability.

Multiresponse Optimization of Selective Laser Melting Parameters for the Ni-Cr-Al-Ti-Based Superalloy Using Gray Relational Analysis.

The selective laser melting technology is of great interest in the aerospace industry since it allows the implementation of more complex part geometries compared to the traditional technologies. This paper presents the results of studies to determine the optimal technological parameters for scanning a Ni-Cr-Al-Ti-based superalloy. However, due to a large number of factors affecting the quality of the parts obtained by selective laser melting technology, the optimization of the technological parameters of the scanning is a difficult task. In this work, the authors made an attempt to optimize the technological scanning parameters which will simultaneously correspond to the maximum values of the mechanical properties ("More is better") and the minimum values of the dimensions of the microstructure defect ("Less is better"). Gray relational analysis was used to find the optimal technological parameters for scanning. Then, the resulting solutions were compared. As a result of the optimization of the technological parameters of the scanning by the gray relational analysis method, it was found that the maximum values of the mechanical properties were achieved simultaneously with the minimum values of the dimensions of a microstructure defect, at a laser power of 250 W and a scanning speed of 1200 mm/s. The authors present the results of the short-term mechanical tests for the uniaxial tension of the cylindrical samples at room temperature.

Investigation on the Air Permeability and Pore Structure of Concrete Subjected to Carbonation under Compressive Stress.

Concrete structures have to withstand the combined effects of external load and environmental factors. Therefore, it is meaningful to study the durability of concrete under compression and carbonation. The air permeability coefficient (kAu) and pore structure of concrete under uniaxial compression and carbonation were measured by the Autoclam method and mercury intrusion porosimetry (MIP). The Autoclam test results showed that the concrete kAu changed in a concave parabolic manner with the compressive stress level, and the inflection point of the stress level was 45%. The MIP results showed that the characteristic pore structural parameters (porosity, average pore diameter, median pore diameter by area, and median pore diameter by volume) first decreased and then increased with the stress level change. The change in concrete microstructure was a result of the combined effect of pore filling, decalcification, and densification, as well as the split effect. The key pore structural parameters affecting kAu were confirmed using gray relational analysis (GRA). The top three parameters with the highest correlation with the carbonated concrete kAu were porosity (gray relational grade γi = 0.789), median pore diameter by volume (γi = 0.763), and proportion of transition pore volume (γi = 0.827). Furthermore, the regression analysis showed a good linear relation between kAu and the important pore structural parameters.

Spatial Pattern of Technological Innovation in the Yangtze River Delta Region and Its Impact on Water Pollution.

The impact of technological innovation on water pollution is an important parameter to determine and monitor while promoting and furthering a region's economic development. Here, exploratory spatial data analysis was used to analyze: the spatial patterns of technological innovation and water pollution in the Yangtze River, the changes in technical innovation and the resulting changes in water pollution, and the impact of technological innovation on water pollution. The following major inferences were drawn from the obtained results: (1) The spatial pattern of innovation input has a single-center structure that tends to spread. The patent innovation output has evolved, from a single spatial pattern with Shanghai as the core to a diffusion structure with three cores-Hangzhou, Shanghai, and Nanjing. (2) The aggregation mode of water pollution has evolved from the original "Z" mode to a new mode of core agglomeration, and water pollution is constantly being reduced. (3) The trends of change in patent innovation output and innovation input are roughly the same, while the trends of both and that of water pollution are contrary to each other. (4) The correlations between innovation input, patented innovation output, and water pollution are relatively low. From the perspective of spatial distribution, the number of cities with medium and high levels of gray correlation with water pollution is the same.

Integrating Taguchi Method and Gray Relational Analysis for Auto Locks by Using Multiobjective Design in Computer-Aided Engineering.

In automobiles, lock parts are matched with inserts, and this is a crucial quality standard for the dimensional accuracy of the molding. This study employed moldflow analysis to explore the influence of various injection molding process parameters on the warpage deformation. Deformation of the plastic part is caused by the nonuniform product temperature distribution in the manufacturing process. Furthermore, improper parameter design leads to substantial warpage and deformation. The Taguchi robust design method and gray correlation analysis were used to optimize the process parameters. Multiobjective quality analysis was performed for achieving a uniform temperature distribution and reducing the warpage deformation to obtain the optimal injection molding process parameters. Subsequently, three water cooling system designs-original cooling, U-shaped cooling, and conformal cooling-were tested to modify the temperature distribution and reduce the warpage. Taguchi gray correlation analysis revealed that the main influencing parameter was the mold temperature followed by the holding pressure. Moreover, the results indicated that the conformal cooling system improved the average temperature distribution.

A Systematic Analysis of 3D Deformation of Aging Breasts Based on Artificial Neural Networks.

The measurement and prediction of breast skin deformation are key research directions in health-related research areas, such as cosmetic and reconstructive surgery and sports biomechanics. However, few studies have provided a systematic analysis on the deformations of aging breasts. Thus, this study has developed a model order reduction approach to predict the real-time strain of the breast skin of seniors during movement. Twenty-two women who are on average 62 years old participated in motion capture experiments, in which eight body variables were first extracted by using the gray relational method. Then, backpropagation artificial neural networks were built to predict the strain of the breast skin. After optimization, the R-value for the neural network model reached 0.99, which is within acceptable accuracy. The computer-aided system of this study is validated as a robust simulation approach for conducting biomechanical analyses and predicting breast deformation.