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Agarwood essential oil (AEO) holds significant medicinal and economic value. While its antitumor activity is reported in the literature, the active ingredients remain unexplored. In this study, the chemical composition of AEO extracted by steam distillation (SD) and fungal fermentation-assisted SD (FFSD) was evaluated by gas chromatography-mass spectrometry (GC-MS). The antitumor activity was evaluated by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Subsequently, the key active ingredients and targets of antitumor activity were evaluated using grey relational analysis and network pharmacology. The relative content of active ingredients in the AEOs extracted from different Aquilaria trees was compared. GC-MS tentatively identified 32 compounds, primarily sesquiterpenoids and aromatic compounds. Eight components with relative content differences were screened using orthogonal partial least squares-discriminant analysis (OPLS-DA), indicating that α-costal, guaiol, β-santalol may play important roles in the antitumor activity. Both SD and FFSD-extracted AEOs demonstrated the ability to inhibit the proliferation and survival of four cancer cell lines, with slightly stronger inhibitory effects observed in AEO extracted by SD. α-Costal, aristolone, 10-epi-γ-eudesmol, γ-eudesmol, agarospirol, hinesol, guaiol, β-santalol, and 6-isopropenyl-4,8a-dimethyl-1,2,3,5,6,7,8,8a-octahydro-naphthalen-2-ol were antitumor ingredients of AEO. The relative content of total active ingredients in agarwood (Aquilaria malaccensis) essential oil was higher, suggesting higher efficacy. This study confirmed the antitumor activity of AEO and identified its active ingredients. These findings provide a basis for further research on the antitumor mechanism of AEO. [ABSTRACT FROM AUTHOR]

For slope instability caused by rainfall, there are some differences between ideal rainfall conditions and actual rainfall conditions. In order to study the stability of slopes under heavy rainfall, this paper therefore takes the "7.20" special rainstorm in Zhengzhou as an example. Four factors, namely average annual rainfall q, soil permeability coefficient anisotropy kr, water table height hw, and suction friction angle φb, were selected as variables. The finite element method was used to analyze the variation rule of initial pore water pressure (IPWP) at the top and bottom of the slope under various factors during the rainfall process, the limit equilibrium method was used to calculate the safety factor (Fs) after the rainfall, and the grey correlation analysis method was used to analyze the sensitivity of factors affecting slope stability under heavy rainfall. The result shows that the pore water pressure at the top of the slope varies more than that at the bottom of the slope during rainfall. The lower the initial pore water pressure, the lower the safety factor of the slope at the end of rainfall. The sensitivity of each factor to the slope safety factor is in the following order: φb>kr>hw>IPWP. [ABSTRACT FROM AUTHOR]

This study focuses on the Shantou Bay Undersea Tunnel and engages in theoretical research to develop a water inflow prediction formula associated with pore water pressure, building upon Darcy's law. The formula has stronger adaptability. Moreover, Grey Relational Analysis is conducted based on theoretical formulas considering various factors to identify the factors influencing the circumferential water inflow ranking in the tunnel. Subsequently, stability analysis of undersea tunnel waterproof and drainage systems is carried out, considering three forms of waterproof and drainage: full-encapsulation non-discharge, full-encapsulation controlled-discharge, and semi-encapsulation free-discharge. The results indicate that, in cases involving grouting, the water inflow prediction formula correlates with seven factors, including the grouting ring permeability coefficient and tunnel dimensions. Grey Relational Analysis reveals that the three most influential factors affecting water inflow in the undersea tunnel are, respectively, the far-field hydraulic head, tunnel outer diameter, and grouting ring permeability coefficient. Analyzing the seepage field distribution around the tunnel bore, it is observed that grouting has the most significant improvement in the seepage field for the full-encapsulation controlled-discharge form. Regarding water seepage, grouting has the most substantial impact on improving water seepage for the semi-encapsulation free-discharge form. Considering the displacement field, reductions are more pronounced in both the full-encapsulation controlled-discharge and semi-encapsulation free-discharge forms. Therefore, in conjunction with radial grouting, adopting a full-encapsulation controlled-discharge drainage system is more suitable for practical engineering applications. This approach reduces both economic costs and the risk of water inflow in the undersea tunnel. [ABSTRACT FROM AUTHOR]

Internal curing technology involves the integration of internal curing materials into concrete, typically under pre-water storage conditions. This method works by gradually releasing water to increase the internal humidity of the concrete, which enhances the hydration of cementitious materials, reduces self-shrinkage in high-strength concrete (HSC), and improves its overall performance. Commonly used internal curing materials include absorbent resin and lightweight aggregates. However, using these materials in excessive amounts can compromise the strength or durability of the concrete, making it essential to determine the optimal dosage for effective application. When applied to HSC, internal curing helps mitigate shrinkage and enhances frost resistance. As noted, accurately determining the appropriate dosage of internal curing materials is critical to maximizing these benefits. The performance evaluation of internally cured HSC is a multiple-attribute decision-making (MADM) problem, and to address the uncertainties involved in this process, triangular fuzzy neutrosophic sets (TFNSs) are particularly suitable. TFNSs offer a more precise way to represent uncertain information. Grey relational analysis (GRA), a widely used technique in grey system theory, assesses the similarity between sequence curves based on their geometric shapes. In this paper, we introduce a triangular fuzzy neutrosophic number GRA (TFNN-GRA) technique under TFNSs, where no prior weight information is available. Weight values under TFNSs are determined using information entropy. By combining GRA with TFNSs, we propose the TFNN-GRA method and outline the steps for solving MADM problems. Finally, a numerical example is presented to demonstrate the performance evaluation of internally cured HSC, along with comparative studies that highlight the advantages of the TFNN-GRA technique. [ABSTRACT FROM AUTHOR]

In the present study, a smart laminated composite beam with auxetic configurations is considered to improve its energy harvesting capabilities. For this purpose, three different cases of auxetic geometries are considered on the cantilever laminated composite beam near the fixed end, and the piezoelectric patches are attached in bimorph configuration over this auxetic region. The coupled structural and piezoelectric equations are developed based on beam element theory. The principle of minimum potential energy is implemented to solve the equations of motion. Effective Young's modulus and Poisson's ratio of the auxetic geometric region are utilized in the beam model, and the results are validated with three-dimensional finite element solution. An experimental study is carried out to validate the finite element studies. The energy harvesting capability of laminated composite beam has significantly improved by using reentrant auxetic geometry. In addition to auxetic geometry, auxetic cubical inclusions are also considered to study their effect on energy harvesting potential. On validating the results obtained from auxetic geometry and auxetic cubical inclusion cases, some parametric studies are conducted to know the influence of auxetic inclusion dimensions, ply orientations, and thickness ratio on the voltage energy output. It is found that with an increase in the length and thickness of the auxetic geometry, the cross-ply oriented auxetic energy harvester's output potential raised considerably. To obtain the optimum parameters required to enhance average output power and minimize the energy loss factor, grey-relational analysis tool, and artificial neural network-based optimization schemes are implemented. The energy harvesting system with the optimized parameters has shown about 60% improvement in the average power output and conversion efficiency. [ABSTRACT FROM AUTHOR]

Nowadays, sustainable Minimum Quantity Lubrication (MQL) technology has significantly enhanced machinability, surface quality, and productivity comparing to dry machining. Furthermore, it is considered as a key factor that respects the ecological trends in machining and also contributes in reducing the consumption of cutting fluid and machining costs. The present paper brings a comparative research between sustainable dry machining and sustainable MQL machining while turning AISI 52100 steel with CVD coated (GC-2015) metal carbide inserts. First, parametric tests were carried out to evaluate the impact of machining parameters (CS, f, and Doc) on performance factors in terms of tool wear, cutting force, surface roughness, energy consumption, and cutting temperature. Then, a Taguchi L9 (3^3) experimental design was implemented in order to carry out a statistical analysis based on ANOVA and performance modelling (Ra, Fz, Pc, Kc, and MRR) by applying the (RSM) method. Finally, a comparative multi-criteria optimization was performed using the DF method and four other MCDM methods (GRA, EAMR, FUCA, and EDAS) combined with Taguchi's signal-to-noise-ratio (S/N). The results confirmed the effectiveness of MQL technique in enhancing machining performance over dry machining. Furthermore, the EAMR, EDAS, and GRA methods identified the same optimal combination (CS = 300 m/min, Doc = 0.45 mm, and f = 0.08 mm/rev), yielding the best results for (Ra, Kc, and MRR). The FUCA method promotes improvement of energy efficiency during machining by achieving minimal values for (Pc and Fz). Finally, the DF method stands out for its ability to produce balanced results across all performances. [ABSTRACT FROM AUTHOR]

Through the qualitative and quantitative analysis of the economic benefits of the adjustment of agricultural industrial structure in Ningxia Hui Autonomous Region, it provides scientific reference for the optimization and adjustment of agricultural industrial structure and agricultural economic development of the province. The grey relational analysis model is used to determine the correlation degree of a specific industry to the overall agricultural economy of Ningxia, and further calculate the contribution degree, and use the comprehensive comparative advantage index to calculate the comparative advantage of main crops. From 2004 to 2021, the calculated results of correlation degree between planting industry, forestry, animal husbandry, fishery and sideline industry and agricultural economy in Ningxia are 0.907 2, 0.617 5, 0.825 4, 0.797 8 and 0.825, respectively. The annual contribution rates to the total agricultural output value are:- 0.19%, -2.63%, -0.10%, -0.73%, -0.41%, -0.60%, -0.11%, -0.16%, -0.10%, -0.10%, -0.44%, -0.20%, -0.05%, -0.07%, -0.66%, -0.27, -0.35%;the highest RCCA values of rice, wheat, maize, potato and legume are 1.64, 2.35, 1.15, 1.87and 1.63, and the dominant areas are Shizuishan, Shizuishan, Wuzhong, Guyuan and Guyuan, respectively. The correlation between planting industry and agricultural economy is the strongest, indicating that planting industry mainly drives the agricultural economy growth of Ningxia. The contribution of agricultural industrial structure adjustment to agricultural economy is low, and the effect of promoting economy is not significant. [ABSTRACT FROM AUTHOR]

GLARE is a type of laminate material made up of layers of aluminum and fiberglass used in automotive, and aircraft structures like fuselage panels, control surfaces, and wing skins due to their superior specific strength, fatigue, and damage tolerance. The inclusion of nanoclay filler was reported to improve the mechanical properties of the GLARE laminates. However, it is important to investigate the machinability of such laminates to extend their applicability in the industry. The current work optimizes the process parameters of the Abrasive Water Jet Machining (AWJM) process to cut the nanoclay-modified Fiber Metal Laminates (FMLs). The experiments were designed by following Taguchi’s L9 orthogonal array. The influence of factors like the velocity of waterjet, mass flow rate, and stand-off distance of the nozzle against the response such as cutting time and sub-surface delamination of layers were studied. The delamination was measured using the variation in thickness before and after the cutting process. The changes in the cutting surface were analyzed using macroscopic analysis. The study also developed the regression model and conducted ANOVA on generated data. Grey Relational Analysis (GRA) was used to identify the optimum values of input process parameters against multiple responses such as cutting time and delamination. The results revealed that the jet velocity significantly affected the cutting time, whereas the stand-off distance and mass flow rate affected the delamination thickness of the laminates. A slight plastic deformation was noted on the metal surfaces along with irregularities and fiber exposure was observed in the GFRP layers of laminates exhibited low cutting performance. [ABSTRACT FROM AUTHOR]

Although the concept of circular economy is a frequently encountered effective tool of sustainable development, its social dimension, the social circular economy, is a topic that has only begun to be discussed. Assessing the social circular economy performance of European Union countries from the sustainable development perspective is critical for monitoring their progress. In this study, a model that evaluates the social circular economy performances of countries for sustainable development is proposed. The importance weights of the evaluation criteria are determined using the interval-valued intuitionistic fuzzy VIKOR method's linguistic scale. Then , the countries are ranked using the grey relational analysis method. In this study, the social circular economy performance of EU member states for 2021 are investigated with the proposed model. According to the results obtained, social circular economy performances are directly proportional to the success of countries in achieving sustainable development goals. The success rating achieved in this study may vary with the improvement activities of the relevant countries. The proposed model updates the ranking, considering each improvement. The findings of this study can help scholars and policymakers better understand the social circularity capabilities of the European Union member countries in the context of sustainable development. In the limited literature, there is no other study in which the social circular economy performance of EU member countries is measured with the relevant evaluation criteria. A model that can evaluate the social circular economy performances of the European Union member countries is proposed to fill the profound gap in this field. We contributed to the literature with a new model that differs with evaluation criteria, real and current data sets. [ABSTRACT FROM AUTHOR]

The current study proposes a new approach that is a combination of methods: fuzzy and decision-making trial and evaluation laboratory (DEMATEL) and distance-based approximation (DBA) so that decision-makers can determine the relationship structures between criteria, how the criteria affect each other, and the weight of each criterion. From that, managers can quickly and easily evaluate and select the best alternative. A previous study using DEMATEL and grey relational analysis (GRA) is presented as an example. Data from this previous study are used to present the implementation process and results of the proposed method and simultaneously show the results of the current problem solved by the fuzzy DEMATEL—TOPPSIS (technique for order of preference by similarity to ideal solution) method. The comparison of results between three methods including DEMATEL—GRA, fuzzy DEMATEL—TOPPSIS, and fuzzy DEMATEL—DBA is performed to demonstrate the efficiency of the proposed method. The results show that there is a slight difference in weights between fuzzy DEMATEL and DEMATEL but the error is extremely low. In addition, the correlation of results between methods is very high. Particularly, correlation coefficients between fuzzy DEMATEL and DEMATEL, between fuzzy DEMATEL—TOPPSIS and fuzzy DEMATEL—BDA, and between DEMATEL—GRA and fuzzy DEMATEL—BDA are 0.99, 0.95, and 0.78 respectively. Finally, all three methods suggest alternative 4 as the best option. [ABSTRACT FROM AUTHOR]

The bone plates used in surgery to assist in fracture healing are often manufactured by metal injection molding (MIM) using a feedstock material consisting of metal powder and polymer binder. However, if the local powder concentration is too low or uneven, black lines may be formed, which impair the product appearance. Furthermore, if the melding temperature is too low, it can lead to meld lines and reduced mechanical properties. Accordingly, this study combines mold flow analysis simulations with the single-objective Taguchi robust design method to determine the MIM processing conditions that optimize the powder concentration and melding temperature. Grey relational analysis (GRA) is then used to establish the processing conditions that simultaneously optimize both MIM objectives. It is found that the processing conditions determined through GRA provide a significant improvement over the original design; however, the experimental outcomes are poorer than those achieved through the single-objective Taguchi experiments since the melt temperature effect suppresses that of all the other processing conditions. Consequently, a robust multi-criteria optimization (RMCO) technique is employed to improve the optimization outcome by identifying the dominant factors in the MIM process and fixing them at optimal levels to redesign the Taguchi experiments to optimize the non-primary factors. It is shown that the RMCO method eliminates interference between the multiple factors and hence provides an improved multi-objective optimization outcome. Overall, the integrated framework proposed in this study advances the optimization of the MIM process for bone plates and leads to improved product quality and performance. [ABSTRACT FROM AUTHOR]

Mode I fracture toughness is the most common amongst the three fracture modes because of its applications in rocks/materials engineering. There are different experimental methods that are available for its measurements and the selection of the available procedures to be used is usually a difficult task and highly multi criteria in nature. Therefore, this study proposed novel applications of two fuzzy-based multi criteria decision making (MCDM) methods for prioritising the experimental procedures. Thirteen different experimental methods were identified and evaluated under three different criteria by the experts. The weights were computed using both expert-assigned weights to each criterion and the fuzzy intuitionistic entropy measure obtained weights. This study reveals that ISRM-suggested cracked chevron notched Brazilian disc method is the most preferred follow by the semi-circular bend specimen and Brazilian disc method. The Pearson's correlation between the models is very strong (˃ 0.9), indicating that either of the two proposed approaches is suitable for this purpose. The sensitivity analysis was conducted by generating twenty-one sets of weights and the outcome ranked ISRM-suggested cracked chevron notched Brazilian disc, the most suitable follow by semi-circular bend specimen and Brazilian disc methods. The correlations amongst the MCDM methods for the sensitivity analysis are also very strong as previously observed. This study shows that the proposed models are suitable in prioritising the most appropriate experimental procedures for mode I fracture toughness. Highlights: Experimental procedures for mode I fracture toughness are found in the literature but users are facing difficulties in selecting the most suitable. Novel fuzzy TOPSIS and fuzzy GRA MCDM methods are used for selecting the best experimental procedure. The ISRM-suggested cracked chevron notched Brazilian disc method is found to be most suitable by the novel methods. [ABSTRACT FROM AUTHOR]

Europe and the people without history (EPWH), published in 1982, challenged anthropology's focus on localism, synchronism, and culturalism, providing a meticulous exposition of multiscalar social relationships in motion. Wolf's bundles of "key relationships" of accumulation and social reproduction formed a breakthrough for holistic relational and realist modes of explanation. Wolf's vision remains essential in capturing capitalism's ongoing uneven and combined concoctions. This theme section revisits EPWH's immanent possibilities – cut short by the "cultural turn" – through critical engagement with Wolf's intellectual toolkit and particularly by building on his analysis as practiced in EPWH. It thereby extends Wolf's vision to questions of political ecology, debt and financialization, hidden histories of class struggle, the contradictory unity of theory and practice, and "planning" as a distinct logic of organizing value. [ABSTRACT FROM AUTHOR]

This study aimed to identify and rank the barriers faced by disabled elderly in China while accessing eHealth primary care services. Primary data were collected from the disabled elderly based on technological, individual, relational, environmental, and organizational constructs. The Dynamic Grey Relational Analysis (DGRA) and Multiple-criteria Decision-making (MCDM) based TOPSIS techniques were used to identify and rank the barriers. We found that the most significant barrier was "aging limitation (reduction in hearing, sight, memory, and fine motor control)" in both (DGRA and MCDM) cases. The Kruskal-Wallis test was used to investigate the significance of this barrier in different age groups of disabled elderly. We found no significant differences among the three age groups of disabled elderly, which shows that the barrier "aging limitation (reduction in hearing. sight, memory, and fine motor control) " is the most significant barrier at each age group (when age ≥ 60) of disabled elderly. The average value of Grey Relational Grades (GRGaverage) and the sorting outcomes of the MCDM of the construct individual were higher than those of all other constructs. This study is the first of its kind to apply the DGRA. MCDM and KWT to expose the barriers while accessing eHealth services for the disabled elderly in China. [ABSTRACT FROM AUTHOR]

The evaluation of urban underground space (UUS) suitability involves multiple indicators. Assigning weight to these indicators is crucial for accurate assessment. This paper presents a method for spatially variable weight assignment of indicators using the order relation analysis method (G1-method), the entropy weight method, an improved grey relational analysis (GRA) and a set of spatial weight adjustment coefficients. First, the subjective and objective weights of indicators for engineering geological and hydrogeological conditions were determined by the G1-method and entropy weight method, respectively, and their combined weights were then obtained using the principle of minimum discriminatory information. This study highlighted the impact of surface restrictions, such as buildings, on UUS, and the degree of the influence of these buildings gradually decreased with the increase in depth of the rock and soil mass in UUS, which resulted in changes in weights of indicators with depth. To address this issue, a coefficient was defined as the standardized value of the ratio of additional stress applied by restrictions to the self-weight stress of soil at the same depth to modify the combined weights so that all weights of indicators could vary in space. Finally, an improved GRA was used to determine the suitability level of each evaluation cell using the maximum correlation criterion. This method was applied to the 3D suitability evaluation of UUS in Sanlong Bay, Foshan City, Guangdong Province, China, including 16 evaluation indexes. This study comprehensively considered the influence of multiple factors, thereby providing reference for evaluating the suitability of UUS in big cities. [ABSTRACT FROM AUTHOR]

Sandwich structures are light weight structures with high strength to weight ratio mostly applicable in aerospace, automotive and, shipbuilding industries. In this study, the aluminium honeycomb core sandwich structure is investigated under flexural test to find the effects of honeycomb core parameters such as cell size, cell wall thickness and core height. Flexural tests such as three point and four point bend test were performed as per ASTM Standard D7250 to evaluate the flexural properties like stiffness and core shear modulus. Taguchi's design of experiment (DOE) has been used to find the effect of structural parameters of the honeycomb core. Since this structure requires the enhancement in properties and reduction in weight, so multi response analysis has been performed by using grey relational analysis. Results shows that the cell size is the most influencing factor followed by core height. Cell wall thickness shows positive effect on flexural properties, but add more weight to the structure. Finally, these findings were confirmed by finding the percentage contribution of structural parameters by Analysis of Variance. [ABSTRACT FROM AUTHOR]

Resource-depleted cities face challenges of land structure imbalance and ecological environmental degradation, necessitating relevant research. Clarifying the land use evolution path and exploring the rationality of urban expansion are of significant importance for the sustainable development of resource-depleted cities. This study employs a comprehensive approach utilizing the land use transfer matrix, expansion intensity, expansion speed, and the equal fan analysis method to investigate the evolution characteristics of construction land in Puyang, a typical resource-exhausted city in China, from 1990 to 2020. Additionally, it identifies the driving factors based on a comprehensive approach combining the variance inflation factor (VIF), grey relational analysis, and Pearson correlation analysis. The main findings include the following: (1) From 1990 to 2020, the cultivated land area in Puyang decreased by 181,296 hectares, while the newly added construction land amounted to 24,846.30 hectares, primarily converted from cultivated land. (2) Puyang comprises five counties and one district. Among them, Hualong District exhibited the highest expansion intensity, speed, and area, whereas Taiqian County showed the lowest. This disparity is attributed to resource-centered land development and utilization. (3) From 1990 to 2020, urban expansion in Puyang primarily concentrated in the northeast direction, exhibiting a concentric outward expansion pattern. (4) Socioeconomic factors positively influenced the expansion of construction land, with the "year-end total population" having the most significant impact. Conversely, land use and natural resource factors negatively impacted construction land expansion, with "cultivated land area" being the most prominent. Additionally, policy and institutional frameworks played a regulatory and restrictive role in the evolution of construction land, while topography and location served as fundamental conditions for urban expansion. This study provides methodologies for sustainable development research in resource-exhausted cities and offers a foundation for land use planning research in resource-based regions of China. [ABSTRACT FROM AUTHOR]

This study presents a comprehensive investigation into optimizing Tungsten Inert Gas (TIG) welding parameters to enhance the mechanical performance of the widely used Al-6061 T6 alloy, specifically in a double V joint configuration with a plate thickness of 6 mm, for aerospace applications. The Taguchi method was employed to design the experiments, providing a robust framework for analyzing the influence of the electrical current, voltage, and gas flow rate on weld quality. Additionally, a Grey Relational Analysis (GRA) and an Analysis of Variance (ANOVA) were used to validate the optimal welding parameters and quantify the significance of each factor. The optimized parameters were determined to be an amperage of 180 A, a voltage of 18 V, and a gas flow rate of 10 L/min, resulting in significant improvements of up to 40% in tensile strength and 23% in hardness, demonstrating the effectiveness of the optimized conditions. The findings provide valuable insights into welding metallurgy, offering practical guidelines for enhancing high-performance welded joints in critical industrial applications. This study underscores the potential of combining Taguchi, GRA, and ANOVA methodologies to achieve superior mechanical properties and reliability in welded structures. [ABSTRACT FROM AUTHOR]

The increasing adoption of electric vehicles offers a way to combat the harmful impacts of climate change and to improve city living standards. Yet limited access to and lack of consistency among electric vehicle charging stations present obstacles for electric vehicle owners. This study advocates for an approach that positions the preferences of electric vehicle drivers first when choosing an electric vehicle charging station. By considering relevant factors to electric vehicle drivers and treating the problem as a grey system where certain information is known while other aspects are unknown, this research aims to empower users to make decisions aligned with their needs. The best–worst method is employed to assign preferences allowing electric vehicle users to make informed choices based on their priorities. The grey relational analysis method is utilized to rank electric vehicle charging stations based on user preferences. The best–worst method-grey relational analysis approach, as shown by examples, efficiently assists electric vehicle users in choosing the optimal electric vehicle charging station. This study acknowledges and incorporates the often-overlooked perspectives of electric vehicle drivers into a user-centric solution in existing research models. The gained insights carry significance for managing transportation and energy systems and designing user-friendly applications pertaining to electric vehicle charging station selection. [ABSTRACT FROM AUTHOR]

With the rapid development of logistics, the categories of goods and the frequencies of train transportation in railway freight have increased significantly. The volatility and uncertainty of railway freight transportation have become even greater. Accurately predicting railway freight volume in the medium to long term has become increasingly challenging. On the basis of traditional prediction models, this paper introduces the concepts of interval and probability prediction, and proposes a temporal convolutional network (TCN)‐bi‐directional long short‐term memory (BiLSTM) interval prediction method for medium and long‐term railway freight volume. The method uses grey relational analysis for data dimensionality reduction and feature extraction, and TCN, BiLSTM, and quantile regression for modelling. Through a case study of freight transportation on the Shuohuang Railway, the results show that the TCN‐BiLSTM model achieves higher accuracy in point prediction and better performance in interval prediction compared to other general prediction models. The interval prediction can provide references for freight volume fluctuations in periods with significant volatility, which can assist railway transportation companies in better scheduling and planning based on such information. [ABSTRACT FROM AUTHOR]

There are significant lithological and stress differences between continental shale layers, posing challenges for hydraulic fractures (HFs) to propagate through the formations, leading to weak fracture effects. To address this, this article adopts the finite element and cohesive force element methods to formulate a three-dimensional numerical model for hydraulic fracture (HF) propagation through layers, considering interlayer lithology and stress variations. The accuracy of the model was verified by physical experiments, and the one-factor analysis method was used to creatively reveal the complex mechanism of the effect of geological and engineering variables on the diffusion of HFs in continental shale reservoirs. The results show that high interlayer stress difference, high interlayer tensile strength difference, low interlayer Young's modulus difference and large interlayer thickness are not conducive to the penetration of HFs, but increasing the injection rate and the viscosity of fracturing fluid can effectively improve the penetration of HFs. The influence ranking of each factor was determined using the grey relational degree analysis method: interlayer stress difference > interlayer Young's modulus difference > interlayer tensile strength difference > interlayer thickness > injection rate > fracturing fluid viscosity. [ABSTRACT FROM AUTHOR]

Block W is a typical tight oil reservoir, generally requiring artificial fracturing to achieve productivity. Consequently, conventional reservoir flow unit studies cannot objectively characterize the properties of tight oil reservoirs after fracturing. This paper integrates both the geological features and dynamic development characteristics of Block W, using Grey Relational Analysis (GRA) to select permeability, sand body thickness, mud content, and porosity as the key static parameters for defining flow units in tight oil reservoirs. The fluid injection intensity is selected as a critical artificial fracturing parameter. Based on these static and artificial fracturing parameters, a comprehensive characterization approach, the entropy weight–AHM method, is proposed to analyze flow units in tight oil reservoirs. The reliability of this method is validated through both production dynamics and geological features. Applied to Block W, this methodology establishes an evaluation standard for the compatibility of fracturing measures with reservoir characteristics and provides directions for adjusting stimulation treatments based on the compatibility levels. The findings deepen the understanding of the geological characteristics of the Block W tight oil reservoir and offer practical guidance for subsequent development adjustments. Additionally, this study serves as a valuable reference for characterizing flow units in tight reservoirs. [ABSTRACT FROM AUTHOR]

This article has made an approach towards the multipass turning of AISI 4340 alloy steel with minimum quantity of coolant to determine the Optimal Turning Parameters for simultaneous maximisation of material removal rate and minimisation of surface roughness. Nine experimental runs were planned according to Taguchi's Design of Experiments and performed on Computer Numerically Controlled Lathe Machine with high carbon steel as a tool. The mathematical models developed for surface roughness and material removal rate at different levels of speed, DOC & feed rate are considered as objective functions. Less than 5% error was observed when experimental results were compared with Regression and ANN Models for both responses. A multi-objective genetic algorithm and a Grey relational analysis were used to determine the optimal turning parameters and the results were validated experimentally. The MOGA provides the best optimal parameters for the simultaneous achievement of SR minimisation and MRR maximisation. Results reveal that speed and feed rate have a significant effect on responses. The Pareto Front Plots extracted from MOGA provide the minimum Ra value, 2.32 µm and for the same point, maximum MRR is 6894.22 mm3/min. However, the experimental method could not meet this Ra value, but the recorded minimum was 2.67 µm and the MRR was 6544.79 mm3/min. [ABSTRACT FROM AUTHOR]

Lightweight alloys play a vital role in the development of automotive, biomedical and aerospace industries as well as other industrial sectors. The current study investigates the machinability of AZ61 magnesium alloy within a vegetable-oil-based MQL environment through high-speed orthogonal cutting. A tool wear and chip morphology examination are conducted along a full factorial experimentation to allow for adequate machinability testing. The usage of Grey Relational Analysis was invoked to allow for a multi-variant optimisation of input parameters such as MQL flow rate, cutting speed, and feed based on output responses, such as chip compression ratio, chip segmentation ratio, tool-chip contact length, and shear angle as well as tool wear evolution. Through the analysis of the formulated signal-to-noise data, it was found that the optimal cutting parameters were an MQL flow rate of 80 ml/h, cutting speed of 250 m/min and feed of 0.3 mm/rev. The optimal cutting conditions resulted in a Grey Relational Grade improvement of 0.177 as compared to the referenced experimental trail. The analysis of variance further concluded that the feed was the highest contributing input parameter at 38.04% followed by the MQL flow rate and the cutting speed. [ABSTRACT FROM AUTHOR]

Performance safety is one of the important goals for the high-quality development of modern performance services. The in-service stage suspension equipment that has been put into use is one of the most frequently used and most closely related stage machinery in performances, and there are often significant safety hazards during its use. In response to the current lack of safety risk assessment methods and incomplete assessment techniques for in-service stage suspension equipment, this paper proposes a safety risk assessment method for in-service stage suspension equipment based on grey fuzzy comprehensive evaluation, with professional theaters as the target scenario. This method first identifies risk factors based on Failure Mode and Effects Analysis (FMEA), then uses the grey relational analysis (GRA) method for risk factor analysis, and finally adopts the fuzzy comprehensive evaluation (FCE) method to achieve safety risk level assessment. By constructing and analyzing an evaluation model for professional theater stage suspension equipment, the safety risk levels and corresponding safety risk factor rankings of performance accidents such as electric shock, falling, and failure can be obtained, and measures to reduce risks can be provided based on the most important risk factors. The research results show that more attention should be paid to the influence of human factors in the safety assessment and detection of in-service stage suspension systems. The research in this article is of great significance for improving the safe use of in-service stage suspension equipment, enhancing the level of performance safety management, and improving the quality of performance equipment services, laying the foundation for the formation of relevant regulatory systems and standards. [ABSTRACT FROM AUTHOR]

With this research, we aim to outline and analyze China's tourism inclusive green growth system and explore its dynamic evolution in terms of economic growth, environmental sustainability, and social inclusiveness. By establishing an evaluation index system and using the entropy weight method, grey correlation, and the coupling coordination model, we analyzed the development level, subsystem correlation strength, and coupling coordination degree of China's tourism inclusive green growth from 2004 to 2022. The main findings are as follows: (1) The tourism inclusive green growth index is generally on an upward trend. The economic growth subsystem is sensitive to emergencies, the social inclusion subsystem demonstrates strong robustness, the environmental sustainability subsystem shows resilience, and the overall system has strong adaptability. (2) From 2004 to 2010, the tourism economy dominated green growth; from 2011 to 2016, the three pillars of tourism inclusive green growth were driven in a coordinated manner; from 2017 to 2018, social inclusion dominated green growth; from 2019 to 2020, the epidemic caused fluctuations; and from 2021 to 2022, economic recovery became the main driving force. (3) From 2004 to 2022, the coordination among the tourism economy, social inclusion, and environmental sustainability significantly improved, especially after 2015. This research emphasizes the balance among economy, society, and environment in China's tourism development and promotes the realization of multi-dimensional win–win results. [ABSTRACT FROM AUTHOR]

The storage period of paddy is a critical factor affecting rice quality, and it is still unclear how fresh rice noodles, primarily made from paddy, respond to changes in the storage period. To elucidate the relationship between the paddy storage period and the quality of fresh rice noodles, this study used fourteen rice varieties as materials and set up three paddy storage periods (six months, nine months, and twelve months). It explored the quality variation patterns of fresh rice noodles processed from these paddies and analyzed the relationship between the two in conjunction with rice quality. The results indicated that fresh rice noodles produced from paddies stored for nine months exhibited superior quality compared to the other two storage periods. Grey relational analysis and correlation analysis confirmed that this was primarily attributed to changes in the gel consistency of the paddy. When the paddy was stored for nine months and the rice gel consistency was approximately 32 mm, the quality of the fresh rice noodles produced was optimal, serving as an important basis for selecting raw materials for fresh rice noodles. [ABSTRACT FROM AUTHOR]

Ceramic materials that find their applications in die extrusion and the balls used in bearings have a longer service life compared to that of traditional materials. Since ceramic materials are having high hardness properties, they cannot be machined traditionally, because traditional machining processes rely on the relative hardness of the tool material to the workpiece material. However, electric discharge machining aids in the machining of ceramic composites with good surface integrity performed by the copper electrodes. As a result, Spark Erosion Machining was used to investigate the geometrical tolerance of Si3N4-TiN composites. Electric discharge machining parameters range over five levels, like current from 2 to 6 A, voltage from 30 to 50 V, dielectric pressure (kg/cm2) from 16 to 24 kg/cm2, pulse on time (µs) from 15 to 19 μs, and pulse off time (µs) from 7 to 11 μs have been analyzed through an L25 orthogonal array. Main effect plots and two-dimensional and three-dimensional interaction plots have been drawn to investigate the effect of the input parameter on the output parameters like circularity, cylindricity, perpendicularity, runout, top radial overcut, and bottom radial overcut. The grey relational analysis is employed in finding the significant parameters through analysis of variance, and for each model, the regression coefficient is found. The optimal input parameters for the desired output parameters are found to be a current of 5.855 A; pulse-on time of 16.55 µs; pulse-off time of 7.22 µs; dielectric pressure of 16.32 kg/cm2; and a voltage of 40.3729 V. This research will help to enhance the geometric accuracy and precision of machined holes in Si3N4-TiN composites. The results are finally estimated using a residual data analysis, which shows that spark erosion can be improved. [ABSTRACT FROM AUTHOR]

Cauliflower is an important winter crop grown in India, its curds are rich in nutritional profile, containing valuable minerals and vitamins. However, cauliflower harvesting is mainly accomplished by hands, which is time-consuming and requires a high labour force. On the other hand, most developed cauliflower harvesters are once over or single pass type, which harvests all plants irrespective of their maturity. So, the selective harvester could improve the cauliflower curds yield, and then decrease the labour requirement. To improve the cutting performance of the selective cauliflower harvester, the working parameters of the chainsaw cutting mechanism need to be considered and optimized. This research investigates the impact of cutting height, feed (push) force, and cutting speed on the efficiency of the cutter during harvest. The Taguchi approach, together with grey relational analysis (GRA), was employed to identify the most favorable combination of operational parameters. In addition, the variance analysis was conducted to statistically examine the impact of multiple parameters. The findings indicated that the feed force was the major parameter that influenced the cutting force, splitting failure levels, and cutting time. The most effective parameter combination consisted of a cutting height of 15 mm, a feed force of 10 N, and a cutting speed of 5 m/s. The grey relational grade of the ideal parameter combination has shown a 0.322 increase in comparison to the grade achieved with the initially selected parameter combination. This setting was further incorporated in the developed selective cauliflower harvester to improve the performance of its cutting mechanism. [ABSTRACT FROM AUTHOR]

This study investigates the optimization of wire electrical discharge machining (WEDM) parameters for microchannel machining of aluminum alloy Al 6061 with improved mechanical properties, which is crucial for various industries. This investigation for microchannel fabrication considers four response parameters: material removal rate (MRR), surface roughness (SR), tool wear rate (TWR), and spark gap (SG), alongside four input parameters: pulse on time (Ton), sparking gap voltage (SGV), wire tension (WT), and wire feed rate (WFR). The selected levels for the experiment are, Ton 105, 115, and 125μs, SGV 10, 25, and 40 volts, WT 6, 8, and 12kgf, and the WFR 2, 4, and 6m/min. By examining Ton, SGV, WT, and WFR, the research identifies optimal conditions using Taguchi-based grey relational analysis (GRA). The findings highlight the importance of parameters such as Ton of 105μs, SGV of 40 volts, WT of 8kgf, and WFR of 4m/min for machining Al 6061-based microchannels, offering valuable insights for future manufacturing endeavors. This research also incorporates the morphology study of machined Aluminium alloy microchannel. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM), also known as 3D printing, is a recent innovation in manufacturing, employing additive techniques rather than traditional subtractive methods. This study focuses on Directed Energy Deposition (DED), utilizing a blend of nickel-based superalloy IN 718 and stainless steel SS316 powders in varying ratios (25%+75%, 50%, and 75%+25%). The objective is to assess the impact of process parameters on quality and optimize them. Mechanical properties of the different powder mixtures are compared. In the study, Taguchi-grey relational analysis is employed for parameter optimization, with four key factors identified: laser power, overlap ratio, powder feed rate, and scanning speed, affecting cladding efficiency, deposition rate, and porosity. Verification experiments confirm optimization repeatability, and further fine-tuning is achieved through one-factor-at-a-time experiments. Optimized parameters yield varied tensile properties among different powder mixtures; for example, a 25% SS316L and 75% IN718 blend demonstrates the highest ultimate tensile strength (499.37 MPa), while a 50% SS316L and 50% IN718 blend exhibits the best elongation (13.53%). This study offers an effective approach for using DED technology to create mixed SS316 and IN718 powders, enabling tailored mechanical performance based on mixing ratios. [ABSTRACT FROM AUTHOR]

ABSTRACT Batocera horsfieldi is a major wood‐boring pest in China's timber and economic forests, belonging to the order Coleoptera and the family Cerambycidae. This study headspace solid‐phase microextraction and gas chromatography–mass spectrometry (GC–MS) were used to analyse the volatile components of B. horsfieldi supplementary feeding host plants, and fingerprint profiles were established. The results revealed that the five plants contained 21, 18, 22, 16 and 17 volatile compounds, mostly terpenes, aldehydes and alcohols, along with trace amounts of furans, ketones and ethers. The terpene compounds were mainly monoterpenes and sesquiterpenes. The results of hierarchical cluster analysis (HCA) and principal component analysis (PCA) were consistent. Five common peaks were identified in these host plants, with (E)‐2‐hexenal, caryophyllene, (E)‐cinnamaldehyde, nonanal, and 3,7‐dimethyl‐1,6‐octadien‐3‐ol being the shared volatile components among the five plants. The mantel test, correlation analysis and grey relational analysis indicated that temperature and precipitation are important factors affecting the content of volatile components. These analytical results provide a basis for using plant volatiles as attractants to control B. horsfieldi. [ABSTRACT FROM AUTHOR]

AbstractTo reduce the pressure drop of diesel particulate filter (DPF) as well as improve its collection efficiency. A mathematical model of DPF pressure drop and capture efficiency was established. This research systematically investigates the effects of channels per square inch (CPSI), wall thickness, and carrier ratio on DPF performance through grey relational analysis (GRA) and polynomial approximation algorithm (PAA). The findings reveal that DPF exhibits lower pressure drop and higher collection efficiency in the case where the carrier ratio, wall thickness, and CPSI are within the ranges of 1.40 to 1.53, 9.8 to 10.5 mil, and 200 to 300, respectively. Particularly, at a carrier ratio of 1.52 and a wall thickness of 10.38 mil, the pressure drop reaches a minimum value of 4.23 kPa, with a collection efficiency of 90.28%. Meanwhile, at a carrier ratio of 1.52 and a CPSI of 200, the pressure drop reaches a minimum value of 4.17 kPa, with a collection efficiency of 90.21%. The model expressions for pressure drop and collection efficiency derived from the PAA are: y1=51.19+3.815x1−8.726x2+3.794x12−1.735x1x2+0.524x22, and y2=0.383+0.105x1+0.085x2+0.032x12−0.016x1x2−0.0032x22. The foregoing models exhibit excellent predictive accuracy and goodness of fit for the DPF performance. Under the interactive influence of carrier ratio and wall thickness, the root mean square errors (RMSE) for pressure drop and collection efficiency are 0.0110 and 0.0002, respectively, with corresponding goodness of fit values of 0.9996 and 0.9985. As revealed by the GRA results, wall thickness exerts the most significant impact on DPF performance, presenting a GRG of 0.84 for filtration efficiency and 0.79 for pressure drop. The overall influence on both collection efficiency and pressure drop follows the descending order: wall thickness > carrier ratio > CPSI. This work has important engineering significance for optimizing the DPF capture performance and extending its working time. [ABSTRACT FROM AUTHOR]

To gain a scientific understanding of the cross-system impact of coastal zones and promote the sustainable development and protection of coastal areas, we constructed a spatial benefit evaluation system that encompassed both terrestrial and marine systems, focusing on the ecological, economic, and social dimensions. We employed the entropy method, moving average method, and Mann-Kendall trend test to quantitatively characterize the spatial benefits of the coastal zone in Fujian Province, China, and the evolution of the marine climate from 2005 to 2020. Building on this, the grey relational analysis method was applied to investigate the correlation between spatial benefits and marine climate and to explore the trends and magnitude of the impact of marine climate on spatial benefits. During the study period, the spatial benefits of the coastal zone in Fujian Province exhibited a fluctuating pattern of an initial increase followed by a decrease, with spatial benefits varying among cities. The role of the economic system in enhancing spatial benefits was not considerable. Changes in the marine climate aligned with the global warming trend, with the most considerable changes observed in sea level and tropical cyclone frequency and intensity, which are sensitive to human activities. There was a high degree of correlation between coastal zone spatial benefits and marine climate, with seawater salinity being most closely related to spatial benefits, while tropical cyclones showed the weakest correlation. The results of this study support sustainable development efforts in coastal zones. [ABSTRACT FROM AUTHOR]

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Failure Modes, Effects, and Criticality Analysis (FMECA) is a commonly used method for analyzing system reliability. It is frequently applied in identifying weak points in the reliability of CNC machine tools. However, traditional FMECA has issues such as vague descriptions of risk factors, equal treatment of risk factors, and unclear directions for improving weak points. In response to the issue of vague descriptions of risk factors, this paper further expands severity (S) into machine hazard (M) and personal hazard (P), and subdivides detectability (D) into functional structural complexity (D1) and detection cost (D2). In addressing the issue of treating risk factors equally, this paper integrates Distance Analysis Method (DAM) and Grey Relational Analysis (GRA) to propose Distance-Grey Relational Analysis (D-GRA). Subsequently, based on the D-GRA method, the weights of each risk factor were determined by comprehensively considering expert system scores and actual economic loss indicators. In response to the issue of unclear improvement directions for weak points, this paper introduces the BCC model. It treats common failure modes of CNC machine tools as decision-making units within the BCC model, refines risk factors as input indicators, and evaluates the efficiency values of each decision-making unit based on various actual losses as output indicators. Through efficiency value analysis, it proposes improvement directions for weak points. Then, based on the weights of risk factors and the efficiency values of failure modes, a modified calculation method for the new Risk Priority Number (RPN) is proposed to amend the traditional RPN, This paper takes the electric spindle system of a certain machining center as an example, applies the proposed method to rank common failure modes with the new RPN, and compares it with other RPN calculation methods to verify the rationality of the proposed approach. Finally, it presents improvement directions for reliability enhancement. [ABSTRACT FROM AUTHOR]

This article has been retracted. A retraction notice can be found at . [ABSTRACT FROM AUTHOR]

Defect Density (DD) is a cornerstone metric in software quality assessment, influencing decisions across quality planning, testing strategies, and resource allocation. However, inherent uncertainties within software module data significantly impede accurate prediction of DD. This paper proposes a novel predictive framework that leverages the strengths of grey system theory and fuzzy logic to address data imprecision in software defect measurement. Our approach introduces a fuzzy grey relational similarity metric that capitalizes on the benefits of both fuzzy logic membership functions and grey relational analysis for similarity assessment. We perform a rigorous evaluation comparing our model with eight established machine learning algorithms across 28 publicly available software datasets. The proposed framework demonstrates superior performance, particularly in scenarios characterized by high sparsity levels in the DD variable. We further analyze the model's efficacy across varying data sparsity levels, categorizing datasets into four groups based on sparsity ratios. Our findings reveal the model's dominance over alternative prediction methods in datasets exhibiting high and very high sparsity. Notably, traditional techniques like multi-linear regression and multi-layer perceptron exhibit limitations in handling such challenges within this specific problem domain and data landscape. Conversely, ensemble learning techniques emerge as viable alternatives for datasets with lower sparsity levels. [ABSTRACT FROM AUTHOR]

Copper matte is the product of matte smelting and also the raw material for the production of blister copper through converting processes. Antimony, as a difficult-to-remove impurity in copper matte, significantly influences the grade of copper, the lifespan of anode furnaces in pyrometallurgical refining,and the quality of cathode plates in electrolytic refining. Given the limited research on predictive control of antimony content in copper smelting, and issues such as poor feature selection and prediction results, a predictive model for antimony content in copper matte was developed, utilizing Principal Component Analysis(PCA) and Support Vector Machine(SVM). The model utilized Grey Relational Analysis (GRA) and Principal Component Analysis (PCA) for feature selection and dimensionality reduction, and integrated with a Novel Improved Particle Swarm Optimization(NIPSO) algorithm enhanced by an improved Sine chaos map for SVM optimization. The model was tested, trained, and validated using metallurgical data. Experimental results demonstrate that the PCA-NIPSO-SVM model significantly outperforms PCA-PSO-SVM, PSO-SVM, and standard SVM in predicting antimony content. The evaluation metrics--Mean Absolute Error( MAE), Mean Squared Error (MSE), and Root Mean Square Error (RMSE)--are 0.011 815 5, 0.000 225 6, and 0.015 019 7 respectively. This SVM model, optimized with the improved Sine chaos map-based particle swarm algorithm, effectively predicts the antimony content in copper matte, providing valuable insights for ingredient planning and process control in oxygen bottom-blown copper smelting. [ABSTRACT FROM AUTHOR]

In this work, a multi-response optimization technique has been used to optimize the process parameters considered while conducting the wear tests of fabricated particle-reinforced epoxy composites. The paper signifies the effect of CaSiO3 and WS2 particles reinforced epoxy composite’s performance at different filler wt.% (2 wt.% CaSiO3 and 1, 2.5, 4, 5.5 and 7 wt.% WS2 ), load (30-70 N), and sliding distance (400-2000 m) parameters that are considered while conducting friction and wear tests. Experiments were conducted on a pin-on-disc configuration using an L25 OA through Taguchi's design of experiment for a constant time of 15 min. The results showed that the inclusion of particles improved the material's friction and wear resistance. The optimal combination of parameters was obtained with Taguchi-GRA followed by determining the most influencing factor using the ANOVA tool. The ANOVA tool calculates the percentage contribution of the process parameters. The wear behaviour was optimized to achieve the lowest coefficient of friction and specific wear rate. At a sliding distance of 2000 m and 15 min testing duration, the combination of parameters that yields the best result is a filler content of 2 wt. % CaSiO3 and 5.5 wt. % WS2, along with a load of 70 N. The ANOVA results reveal that the load with a percentage contribution of 50.87% is the most significant parameter followed by filler content (15.63%) and sliding distance (13.55%). A confirmation test is carried out using the optimal control parameters to validate the experimental results. Additionally, the SEM was used to analyse the worn surfaces of epoxy composites. The SEM images reveal the adhesive and abrasive wear mechanism is most prevalent in the observed material. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to investigate the effect of the copresence of ferrous (Fe2+) ions and sodium dodecyl sulfate (SDS) on the activity of an amylase enzyme during the desizing of greige viscose fabric for potential industrial applications. The removal of starches is an essential step before processing the fabric for dyeing and finishing operations. The authors tend to accomplish it in eco-friendly and sustainable ways. Design/methodology/approach: The experiments were designed under the Taguchi approach, and the results were analyzed using grey relational analysis to optimize the process. The textile properties of absorbency, reducing sugars, bending length, weight loss, Tegawa rating and tensile strength were assessed using the standard protocols. The control and optimized viscose specimens were investigated for certain surface chemical properties using advanced analytical techniques including scanning electron microscopy (SEM), X-ray diffraction (XRD) and thermal gravimetric analysis (TGA). Findings: The results demonstrate that the Fe2+ concentration and process time were the main influencing factors in the amylolytic desizing of viscose fabric. The optimized process conditions were found to be 0.1 mm Fe2+ ions, 3 mm SDS, 80°C, 7 pH and 30 min process time. The copresence of Fe2+ ions and SDS promoted the biodesizing of viscose fabric. The SEM, Fourier transform infrared spectroscopy, XRD and TGA results demonstrated that the sizing agent has efficiently been removed from the fabric surface. Practical implications: The amylase desizing of viscose fabric in the presence of certain metal ions and surfactants is a significant subject as the enzyme may face them due to their prevalence in the water systems. This could also support the biodesizing and bioscouring operations to be done in one bath, thus making the textile pretreatment process both economical and environmentally sustainable. Originality/value: The authors found no report on the biodesizing of viscose fabric in the copresence of Fe2+ ions and the SDS surfactant under statistical multiresponse optimization. The biodesized viscose fabric has been investigated using both conventional and analytical approaches. [ABSTRACT FROM AUTHOR]