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In response to the severe lag in tracking the response of the Stewart stability platform after adding overload, as well as the impact of nonlinear factors such as load and friction on stability accuracy, a new error attenuation function and a parallel stable platform active disturbance rejection control (ADRC) strategy combining cascade extended state observer (ESO) are proposed.

First, through kinematic modeling of the Stewart platform, the relationship between the desired pose and the control quantities of the six hydraulic cylinders is obtained. Then, a linear nonlinear disturbance observer was established to observe noise and load, to enhance the system’s anti-interference ability. Finally, verification was conducted through simulation.

Finally, stability analysis was conducted on the cascaded observer. Experiments were carried out on a parallel stable platform with six degrees of freedom involving rotation and translation. In comparison to traditional PID and ADRC control methods, the proposed control strategy not only endows the stable platform with strong antiload disturbance capability but also exhibits faster response speed and higher stability accuracy.

A new error attenuation function is designed to address the lack of smoothness at d in the error attenuation function of the ADRC controller, reducing the system ripple caused by it. Finally, a combination of linear and nonlinear ESOs is introduced to enhance the system's response speed and its ability to observe noise and load disturbances. Stability analysis of the cascade observer is carried out, and experiments are conducted on a six-degree-of-freedom parallel stable platform with both rotational and translational motion.

This research aims to propose a model for the complex decision-making involved in the ecological restoration of mega-infrastructure (e.g. railway engineering). This model is based on multi-source heterogeneous data and will enable stakeholders to solve practical problems in decision-making processes and prevent delayed responses to the demand for ecological restoration.

Based on the principle of complexity degradation, this research collects and brings together multi-source heterogeneous data, including meteorological station data, remote sensing image data, railway engineering ecological risk text data and ecological restoration text data. Further, this research establishes an ecological restoration plan library to form input feature vectors. Random forest is used for classification decisions. The ecological restoration technologies and restoration plant species suitable for different regions are generated.

This research can effectively assist managers of mega-infrastructure projects in making ecological restoration decisions. The accuracy of the model reaches 0.83. Based on the natural environment and construction disturbances in different regions, this model can determine suitable types of trees, shrubs and herbs for planting, as well as the corresponding ecological restoration technologies needed.

Managers should pay attention to the multiple types of data generated in different stages of megaproject and identify the internal relationships between these multi-source heterogeneous data, which provides a decision-making basis for complex management decisions. The coupling between ecological restoration technologies and restoration plant species is also an important factor in improving the efficiency of ecological compensation.

Unlike previous studies, which have selected a typical section of a railway for specialized analysis, the complex decision-making model for ecological restoration proposed in this research has wider geographical applicability and can better meet the diverse ecological restoration needs of railway projects that span large regions.

Accurately identifying the risk of poverty-returning is a complex and critical challenge in current poverty alleviation efforts. However, there is currently no study on evaluation methods for the risk of poverty-returning. This study aims to establish a robust and systematic approach for an evaluation framework for the risk of poverty-returning.

Based on relevant assessment criteria, a maximum deviation method was established to identify the weights of the indicators. A complex evaluation methodology using prospect theory (PT), a q-rung orthopair fuzzy set (QrOFS) and evaluation relying on distance from average solution [EDAS] (QrOFS-PT-EDAS) was developed to evaluate the poverty-returning risks. Some policy recommendations to reduce the risk of poverty-returning have also been put forward.

His study identifies the risk factors of poverty relapse from nine aspects, including natural disasters, accidents and policy-driven poverty relapse. In addressing the evaluation challenge arising from uncertain decision-making, the QrOFS aligns more with people’s thinking habits and expression methods in complex environments. The proposed hybrid evaluation framework accurately measures the poverty-returning risk, which is beneficial for the formulation of policy recommendations.

A scientific and comprehensive assessment system index for poverty-returning is constructed. A hybrid QrOFS-PT-EDAS framework is presented to make the evaluation results more scientific and objective. Several strategic recommendations for reducing the poverty-returning risk are presented. This study offers a novel framework for assessing poverty-returning issues that can be extended to many other areas.

A meat quality grading system is essential to meet consumers' increasingly diversified demand for food quality in the global market. This study aims to determine the effectiveness of the upcoming Chinese quality grading labels and examine the information effect of labeling standards on pork consumption choices.

Using an online survey with choice experiments, this study estimates consumer valuation for the fat thickness of different pork primal cuts by simulating three scenarios. Generalized mixed logit models in WTP space are used to analyze the choice experiment data.

Chinese consumers prefer lean pork to fatty pork and this preference does not vary significantly between primal cuts. Consumer valuation for ungraded high-quality (lean) pork increases after the implementation of the quality grading. Meanwhile, they are willing to pay high premiums for labeled pork (including level 1, 2, 3), and there are higher premiums for pork with higher levels. Besides, incomplete information on labeling standards could achieve more premiums for pork than relatively complete information.

This study pays attention to essential but few-noticed pork quality grading. The findings provide references for pork industry practices and policy-making of the meat quality grading system in China and globally by examining incomplete and relatively complete information effects on consumer choices.

The study aims to investigate consumer preferences across 25 attributes of plant-based milk (PBM) products and examine the key predictors and underlying mechanisms of consumer purchase decisions of PBM alternatives.

This study employed a multidimensional approach to investigate consumer preferences and the determinants of PBM purchasing decisions. Drawing on data from 819 online surveys conducted in the Jing-Jin-Ji region of China in 2021, we measured consumer preferences across 25 specific attributes and other individual characteristics. Purchasing decisions were framed as a two-stage process – the decision to purchase (frequency) and the decision on how much to pay (WTP). The Least Absolute Shrinkage and Selection Operator (LASSO) model was utilized to examine these dimensions separately, and the selected predictors were incorporated into OLS linear and Heckman’s two-stage regression analyses to establish the underlying mechanisms.

The findings indicate that consumers exhibit a strong preference for freshness and the absence of spoilage, followed by taste experiences such as taste and aroma. Preferences for milk preservation significantly increase the purchase frequency of PBM, while preference for calorie content has a negative and significant impact. Preferences for milk preservation, aroma and processing methods can also significantly increase WTP. Preferences vary across PBM categories. Social influence, knowledge and advertising exposure positively impact purchase frequency and WTP. Consumers with low food neophobia tend to be more responsive to product-related factors, such as freshness, calorie content and processing methods, in their purchase decisions.

This study contributes to the extant literature by comprehensively examining the determinants of consumer purchase decisions for PBM alternatives. The findings provide practical implications for marketers and policymakers, highlighting the strategic product attributes, consumer segments and marketing levers that can effectively target and cater to consumer preferences for PBM alternatives.

The purpose of this paper is to solve the diverse and complex problems of flat-knitting sports upper process design, improve the design ability of upper organization, and realize three-dimensional simulation function.

Firstly, the matrix is used to establish the corresponding pattern diagram and organizational diagram model, and the relationship between the two is established by color coding as a bridge to completed the transformation of the flat-knitted sports upper process design model. Secondly, the spatial coordinates of the loop type value points are obtained through the establishment of loop mesh model, the index of two-dimensional and three-dimensional models of uppers and the establishment of spatial transformation relationship. Finally, using Visual Studio as a development tool, use the C# language to implement this series of processes.

Digitizing the fabric into a matrix model, combined with matrix transformation, can quickly realize the design of the flat-knitting process. Taking the knitting diagram of the upper process as the starting point, the loop geometry model corresponding to the element information is established, and the three-dimensional simulation effect of the flat-knitted upper based on the loop structure is realized under the premise of ensuring that it can be knitted.

This paper proposes a design and modeling method for flat-knitted uppers. Taking the upper design process and 3D simulation effect as an example, the feasibility of the method is verified, which improves the efficiency of the development of the flat-knitted upper product and lays the foundation for the high-end customization of the flat-knitted upper.

The aim of this study is to establish the nonlinear dynamics equations of roller bearings with surface faults on outer raceway, inner raceway and rolling elements to analyze the dynamic characteristics of the double row self-aligning roller bearings, and provided theoretical basis for bearing fault diagnosis and life prediction.

First, based on the momentum theorem, the formulas for quantitative calculation of impact load were established, when roller was in contact with the fault of the inner or outer raceway. Then, the fault position piecewise functions and the load-carrying zone piecewise functions were established. Based on these, the nonlinear dynamic equations of double row self-aligning roller bearings are established, and Matlab is used to simulate the faulty bearings at different positions, sizes and rotational speeds. Finally, the vibration test of the fault bearings are completed, and the correctness of the nonlinear dynamic equations of the rolling bearing are verified.

The simulation and test results show that: the impact load increased with the increasing rotate speed and fault size, and the larger the fault size, the longer the impact load existed and the shorter vice versa.

The nonlinear dynamic equation of double row self-aligning roller bearings is established, which provides a theoretical basis for bearing faults diagnosis and fatigue life prediction.

Achieving a zero-carbon city requires a long-term strategic perspective. The authors propose a decision-making model which would take into account the economic, environmental and social impacts for prioritizing the zero-carbon measures for sustainable urban transportation.

An integrated intuitionistic fuzzy gained and lost dominance score (IF-GLDS) model is introduced based on intuitionistic fuzzy Yager weighted aggregation (IFYWA) operators and proposed weight-determining IF-SPC procedure. In addition, a weighting tool is presented to obtain the weights of decision experts. Further, the feasibility and efficacy of developed IF-SPC-GLDS model is implemented on a multi-criteria investment company selection problem under IFS context.

The results of the developed model, “introducing zero-emission zones” should be considered as the first measure to implement. The preference of this initiative offers sustainable transport in India to achieve a zero-carbon transport by having the greatest impact on the modal shift from cars to sustainable mobility modes with a lower operational and implementation cost as well as having greater public support. The developed model utilized can be relocated to other smart cities which aim to achieve a zero-carbon transport. Sensitivity and comparative analyses are discussed to reveal the robustness of obtained result. The outcomes show the feasibility of the developed methodology which yields second company as the suitable choice, when compared to and validated using the other MCDA methods from the literature, including TOPSIS, COPRAS, WASPAS and CoCoSo with intuitionistic fuzzy information.

A new intuitionistic fuzzy symmetry point of criterion (IF-SPC) approach is presented to find weights of criteria under IFSs setting. Then, an IF-GLDS model is introduced using IFYWA operators to rank the options in the realistic multi-criteria decision analysis (MCDA) procedure. For this purpose, the IFYWA operators and their properties are developed to combine the IFNs. These operators can offer a flexible way to deal with the realistic MCDA problems with IFS context.

This paper aims to estimate contact location from sparse and high-dimensional soft tactile array sensor data using the tactile image. The authors used three feature extraction methods: handcrafted features, convolutional features and autoencoder features. Subsequently, these features were mapped to contact locations through a contact location regression network. Finally, the network performance was evaluated using spherical fittings of three different radii to further determine the optimal feature extraction method.

This paper aims to estimate contact location from sparse and high-dimensional soft tactile array sensor data using the tactile image.

This research indicates that data collected by probes can be used for contact localization. Introducing a batch normalization layer after the feature extraction stage significantly enhances the model’s generalization performance. Through qualitative and quantitative analyses, the authors conclude that convolutional methods can more accurately estimate contact locations.

The paper provides both qualitative and quantitative analyses of the performance of three contact localization methods across different datasets. To address the challenge of obtaining accurate contact locations in quantitative analysis, an indirect measurement metric is proposed.

This study aims to investigate the relationship between corporate environmental responsibility (CER) and risk-taking in Chinese A-share listed companies from 2011 to 2020. It seeks to understand the influence of CER on risk-taking behavior and explore potential moderating factors.

A quantitative approach is used, using data from Chinese A-share listed companies over the specified period. Regression analysis is used to examine the relationship between CER and risk-taking, while considering moderating variables such as performance aspiration, environmental enrichment and contextual factors.

The findings indicate that CER positively influences corporate risk-taking, with significant impacts on information asymmetry and corporate reputation. Moreover, positive performance aspiration strengthens the effect of CER on risk-taking, while negative performance aspiration and environmental enrichment weaken this effect. Cross-sectional analysis shows that the positive association between CER and risk-taking is more prominent for firms located in areas with strict environmental regulation, for nonstate-owned firms, and for firms with higher levels of internal control.

This research contributes to the literature by providing insights into the dynamics between CER and risk-taking in the Chinese market context. It expands existing knowledge by considering the influence of performance aspiration on this relationship, offering practical implications for firms seeking to enhance corporate performance through strategic management of environmental responsibilities.