Search Results (69)

Improving forest carbon sink efficiency (FCSE) is the key to mitigating climate change and achieving sustainable forest resource management in China. However, current research on FCSE remains predominantly focused on static perspectives and singular linear effects. Based on panel data from 30 provinces (autonomous regions and municipalities) in China from 2008 to 2022, this study integrated the super-efficiency Slack-Based Measure (SBM)-Malmquist–Luenberger (ML) model, spatial autocorrelation analysis, and dynamic fuzzy set qualitative comparative analysis (fsQCA) to reveal the spatiotemporal differentiation characteristics of FCSE and the multi-factor synergistic driving mechanism. The results showed that (1) the average value of the FCSE in China was 1.1. Technological progress (with an average technological change of 1.21) is the core growth driver, but the imbalance of technological efficiency change (EC) among regions restricts long-term sustainability. (2) The spatial distribution exhibited a U-shaped gradient pattern of “eastern—southwestern”, and the synergy effect between nature and economy is significant. (3) The dynamic fsQCA identified three sustainable improvement paths: the “precipitation–economy” collaborative type, the multi-factor co-creation type, and “precipitation–industry-driven” type; precipitation was the universal core condition. (4) Regional differences exist in path application; the eastern part depends on economic coordination, the central part is suitable for industry driving, and the western part requires multi-factor linkage. By introducing a dynamic configuration perspective, analyzing FCSE’s spatiotemporal drivers. We propose a sustainable ‘Nature–Society–Management’ interaction framework and region-specific policy strategies, offering both theoretical and practical tools for sustainable forestry policy design. Full article

It is essential to establish a normative framework that ensures the harmonious coexistence of humans and animals from legal and institutional perspectives. This study classifies and compares animal welfare policies in welfare states, identifying distinct policy types across different countries. Using fuzzy set ideal type analysis, this study examines seven OECD countries: Austria, Denmark, Germany, South Korea, Sweden, the United Kingdom (UK), and the United States (USA). These countries are consistent with Esping-Andersen’s three welfare state models and actively implement animal welfare policies. This study addresses the limitations of previous studies that focused primarily on animal-related discourses by examining the characteristics of different policy types that integrate two core components of animal welfare policy: animal welfare law and animal welfare systems. This analysis identified four types of animal welfare policies: (1) economic value type (South Korea and the USA); (2) social value type (the UK); (3) rights extension type (Denmark, Germany, and Sweden); and (4) ecological type (Austria). The results show that welfare state animal welfare policies are generally consistent with the ideological characteristics of the welfare system in question. However, Korea presents notable differences, providing valuable insights into its unique approach to animal welfare policy and informing future policy development. Full article

Against the intensifying mismatch between urban and rural land resources, activating farmers’ intentions to revitalize their idle homesteads is a key issue in optimizing land resource allocation and promoting urban–rural integrated development. However, existing studies mostly focus on the marginal effect of a single factor and ignore the synergistic effect of multiple factors, making it difficult to reveal the complex causal logic of farmers’ decision-making. This study aims to explain the causal asymmetry and equivalent path problem in farmers’ revitalized decision-making by capturing the multidimensional interaction mechanism of “external stimulus–mental cognition”. This study integrates the social stratification theory, the theory of planned behavior, and the Stimulus–Organism–Response framework to systematically explore how the interactive configuration of farmer differentiation and cognition from a multidimensional perspective drives the formation of farmers’ willingness to engage in high inventory activities, based on the 881 farmer research data in Shaanxi Province, using fuzzy-set qualitative comparative analysis (fsQCA) methodology. This study found that (1) a single condition cannot independently explain the intentions of farmers to revitalize, and its formation needs to rely on the synergistic linkage of multiple conditions; (2) the configuration of farmers’ high intentions to revitalize includes “wealth capital differentiation–dual cognitive-driven type”, “single cognitive-driven type”, “reputation capital differentiation–single cognitive-driven type”, “wealth capital differentiation–single cognitive-driven type”, which wealth capital differentiation is the common core condition triggering high intention; and (3) the formation of farmers’ low revitalization intentions stems from the insufficient differentiation of farmers and the lack of cognitive elements. Therefore, policymakers should take a holistic perspective in enhancing farmers’ revitalization intentions, focusing on the rational allocation between farmer differentiation and farmers’ cognition. Full article

This paper innovatively proposes the concepts of length, width, and depth for modern agricultural industrial systems. The development level of the modern agricultural industrial system is systematically measured by the length of the agricultural industry chain, the width of agriculture in terms of its overlap with and integration of non-agriculture industries, and the depth of agricultural productive services. Using the fuzzy set qualitative comparative analysis method, 88 main production areas of special and excellent agricultural products in Shanxi, China, are selected as sample objects. The configuration paths of the length, width, and depth of the modern agricultural industrial system impacting farmers’ wage income, operating income, property income, and transfer income are explored. The study found the following: (1) The income level of farmers is jointly influenced by the length, width, and depth of the modern agricultural industrial system, emphasizing that a single factor does not constitute a necessary condition for farmers’ income growth and prosperity. (2) There exist four types of paths through which the modern agricultural industrial system can promote increases in farmer incomes, namely “non-industry length * industry width”, “industry length * non-industry width * non-industry depth”, “non-industry length * industry depth” and “industry length * non-industry depth”, a various types of paths have a differential impact on the structure of farmers’ incomes. (3) The length, width, and depth of the modern agricultural industrial system individually have crowding-out effects on each of a farmer’s four types of income. Full article

Ecotourism comfort is an important way to promote the harmonious coexistence between humans and nature, and it is the concrete implementation of the concept of harmonious coexistence and the theory of “Two Mountains”. Based on the urban comfort theory, the ecotourism comfort level of Chengdu city from 2010 to 2020 was measured. The MCR model and the gravity model were used to extract the potential corridor of ecotourism comfort to identify the core area of ecotourism comfort, and its configuration path was analyzed through a qualitative comparison of fsQCA fuzzy sets. The findings are as follows: (1) The overall level of ecotourism comfort in Chengdu has been improved, and the spatial distribution has a “core-edge” structure, which has obvious characteristics of “polarization leading and common development”. Among them, Wuhou District, Qingyang District, and Longquanyi District are the core areas, and the driving effect on marginal areas is particularly significant. (2) The potential ecological corridors in Chengdu are more densely distributed in the east than in the west, with significant north–south variations within both regions. (3) The core corridors of ecotourism comfort originate from Xinjin District and Longquanyi District, characterized by a banded distribution and primarily concentrated along the southwest–northeast axis. (4) The high level of ecotourism comfort in Chengdu is primarily manifested in five distinct types: “comprehensive drive, resource–transportation synergy, technology–transportation integration, government–led investment, and tourism market–technology linkage”. The research results offer a theoretical basis and scientific reference for enhancing the comfort level of urban ecotourism and comprehensively promoting the sustainable development of ecotourism. Full article

Emotion is an intricate cognitive state that, when identified, can serve as a crucial component of the brain–computer interface. This study examines the identification of two categories of positive and negative emotions through the development and implementation of a dry electrode electroencephalogram (EEG). To achieve this objective, a dry EEG electrode is created using the silver-copper sintering technique, which is assessed through Scanning Electron Microscope (SEM) and Energy Dispersive X-ray Analysis (EDXA) evaluations. Subsequently, a database is generated utilizing the designated electrode, which is based on the musical stimulus. The collected data are fed into an improved deep network for automatic feature selection/extraction and classification. The deep network architecture is structured by combining type 2 fuzzy sets (FT2) and deep convolutional graph networks. The fabricated electrode demonstrated superior performance, efficiency, and affordability compared to other electrodes (both wet and dry) in this study. Furthermore, the dry EEG electrode was examined in noisy environments and demonstrated robust resistance across a diverse range of Signal-To-Noise ratios (SNRs). Furthermore, the proposed model achieved a classification accuracy of 99% for distinguishing between positive and negative emotions, an improvement of approximately 2% over previous studies. The manufactured dry EEG electrode is very economical and cost-effective in terms of manufacturing costs when compared to recent studies. The proposed deep network, combined with the fabricated dry EEG electrode, can be used in real-time applications for long-term recordings that do not require gel. Full article

The “green transformation of the express” delivery industry in this study primarily refers to the adoption of green energy and environmentally friendly technologies in express delivery packaging, transportation, and recycling systems. This transformation can significantly enhance energy efficiency and reduce emissions in the express system, promoting the sustainable development of the entire industry. However, the progress of green transformation in China’s express delivery industry has been impeded by various barriers. To address this, we propose a barrier analysis framework based on the Fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) methodology to explore key obstacles to green transformation in the express industry. Our research aims to answer three main questions: (1) What are the key barriers to green transformation in China’s express delivery industry? (2) How do these barriers interact and influence each other? (3) What strategic measures can be implemented to overcome these barriers? We first compile a list of barriers, innovatively proposing two new ones: “inadequate green standards in the express industry” and “suboptimal green packaging technology”. Considering the ambiguity in expert input and the complex interactions among barriers, we employ fuzzy DEMATEL within an Interval Type 2 Fuzzy Sets (IT2FSs) environment to investigate the significance and causality of these barriers. This approach distinguishes our study from previous research by providing a more nuanced understanding of barrier interactions in the specific context of China’s express delivery industry. Based on our analysis, we identify eight critical barriers and propose corresponding strategic measures. Full article

In the context of escalating environmental and climate concerns, it is imperative for enterprises to embark on carbon emission reduction initiatives. Exploring the driving pathways for corporate low-carbon transformation is crucial for the development of a green economy. In this paper, various configuration pathways that may drive heavily polluting industrial enterprises towards green and low-carbon transformation were investigated based on the Technology–Organization–Environment (TOE) theoretical framework and the fuzzy set qualitative comparative analysis (fsQCA) method. The results indicated the following: (1) the low-carbon transformation of heavily polluting enterprises is the result of the joint action of multiple factors; (2) there are eight pathways that can promote corporate low-carbon transformation, roughly divided into single-factor driving types (including MEA drive, DT drive, and GI drive), dual-factor driving types (DT–ER drive and DT–ESGR drive), and multi-factor driving types (including GI–DT–MEA–ER drive, GI–FS–ER drive, and GI–FS–ESGR drive). It can be concluded that there can be certain substitutions between green technology innovation and digital transformation, and environmental regulations and ESG ratings. (3) GI and DT are crucial to the low-carbon transformation of heavily polluting enterprises, and the latter has a more significant impact on promoting low-carbon transformation. MEA is also worthy of attention. The research conclusions not only provide theoretical support for the low-carbon transformation of heavily polluting industrial enterprises but also have valuable reference significance for other industry enterprises, and even the whole of society, to achieve green sustainable development. Full article

In recent decades, many different governmental and nongovernmental organizations have used lie detection for various purposes, including ensuring the honesty of criminal confessions. As a result, this diagnosis is evaluated with a polygraph machine. However, the polygraph instrument has limitations and needs to be more reliable. This study introduces a new model for detecting lies using electroencephalogram (EEG) signals. An EEG database of 20 study participants was created to accomplish this goal. This study also used a six-layer graph convolutional network and type 2 fuzzy (TF-2) sets for feature selection/extraction and automatic classification. The classification results show that the proposed deep model effectively distinguishes between truths and lies. As a result, even in a noisy environment (SNR = 0 dB), the classification accuracy remains above 90%. The proposed strategy outperforms current research and algorithms. Its superior performance makes it suitable for a wide range of practical applications. Full article

Practice shows that digital platforms could enhance disruptive innovation. Given that digital platforms have always encountered imbalance problems, this study intended to explore which factor configurations could promote disruptive innovation sustainably from the perspective of supply and demand matching. This study constructed a theoretical framework referring to the TOE framework. Based on 25 questionnaires from China, the fuzzy-set qualitative comparative analysis (fsQCA) method was used to explore the configurations of disruptive innovations. This study found the following: (1) None of the five factors in the dimensions of technology, organization, or environment could constitute a necessary condition for enabling disruptive innovation alone. (2) There were four supply and demand matching configurations that could lead to highly disruptive innovation. Based on the homogeneous characteristics of the results, the four paths were divided into “technology-organization driven transition” types and “organization-environment collaborative transition” types. (3) Non-highly disruptive innovation included three specific configurations, all of which lacked the core conditions in technical and organizational dimensions, suggesting the importance of technical and organizational factors for disruptive innovation. This study provides guidance on supply and demand matching for platform enterprises to continuously create disruptive innovation. However, the data from China may limit the results’ applicability to a more expansive setting. Full article

This review study provides a comprehensive analysis of the classification of inventory models, with a focus on incorporating various fuzzy demand functions. The incorporation of fuzzy sets theory within inventory models is highlighted as a significant advancement in the field. The study emphasizes the importance of efficiently locating pertinent publications on this topic, rendering it a valuable resource for individuals interested in exploring inventory models that incorporate fuzzy demand functions. There was a need for a systematic and complete examination of recent breakthroughs in fuzzy inventory management. Our objective was to provide an illuminating overview of the significant developments in this field and offer insights into the probable future directions of research. Our evaluation of various model components has unveiled new and underexplored territories that may warrant further exploration. Perhaps it would be prudent to consider the possibility of establishing simpler models or incorporating qualitative methods into existing models and initiating a discourse on this topic. Full article

The high-quality development of the industrial software industry is of strategic significance to enhancing the core competitiveness of the manufacturing industry and promoting the high-quality development of China’s industrial economy. By integrating the “capital-technology-environment-human” production factor theory and configuration perspective, this paper constructs a comprehensive analysis framework that drives the total factor productivity (TFP) of the industrial software industry. This paper uses 40 typical industrial software firms in 2018–2020 as case samples and uses fuzzy set Qualitative Comparative Analysis (fsQCA) to empirically explore the influencing factors and complex mechanisms that achieve high-quality development of the industrial software industry. It is found that: (1) a single industrial factor is hardly a necessary condition to drive the industrial software industry; (2) there are four paths to achieving high TFP, which are summarized as “technical-human-environmental” balanced driving type, “capital-human-environmental” balanced driving type, “technical-capital” dual driving type, and “capital” single driving type. There are four driving mechanisms. There are also four not-high TFP configurations with asymmetric characteristics; (3) under certain conditions, the combination of capital factors, technical factors, environmental factors, and human factors can drive TFP in an “all roads lead to Rome”. In this process, the government’s attention plays a more universal role. The study not only expands the application scenarios of fsQCA but also provides decision guidelines for the practice of strategic emerging industrialization represented by the industrial software industry. Full article

This paper presents (a) a novel hybrid learning method to train interval type-1 non-singleton type-3 fuzzy logic systems (IT3 NSFLS-1), (b) a novel method, named enhanced Wagner–Hagras (EWH) applied to IT3 NSFLS-1 fuzzy systems, which includes the level alpha 0 output to calculate the output $y$ alpha using the average of the outputs $y$ alpha $k$ instead of their weighted average, and (c) the novel application of the proposed methodology to solve the problem of transfer bar surface temperature prediction in a hot strip mill. The development of the proposed methodology uses the orthogonal least square (OLS) method to train the consequent parameters and the backpropagation (BP) method to train the antecedent parameters. This methodology dynamically changes the parameters of only the level alpha 0, minimizing some criterion functions as new information becomes available to each level alpha $k$. The precursor sets are type-2 fuzzy sets, the consequent sets are fuzzy centroids, the inputs are type-1 non-singleton fuzzy numbers with uncertain standard deviations, and the secondary membership functions are modeled as two Gaussians with uncertain standard deviation and the same mean. Based on the firing set of the level alpha 0, the proposed methodology calculates each firing set of each level alpha $k$ to dynamically construct and update the proposed EWH IT3 NSFLS-1 (OLS–BP) system. The proposed enhanced fuzzy system and the proposed hybrid learning algorithm were applied in a hot strip mill facility to predict the transfer bar surface temperature at the finishing mill entry zone using, as inputs, (1) the surface temperature measured by the pyrometer located at the roughing mill exit and (2) the time taken to translate the transfer bar from the exit of the roughing mill to the entry of the descale breaker of the finishing mill. Several fuzzy tools were used to make the benchmarking compositions: type-1 singleton fuzzy logic systems (T1 SFLS), type-1 adaptive network fuzzy inference systems (T1 ANFIS), type-1 radial basis function neural networks (T1 RBFNN), interval singleton type-2 fuzzy logic systems (IT2 SFLS), interval type-1 non-singleton type-2 fuzzy logic systems (IT2 NSFLS-1), type-2 ANFIS (IT2 ANFIS), IT2 RBFNN, general singleton type-2 fuzzy logic systems (GT2 SFLS), general type-1 non-singleton type-2 fuzzy logic systems (GT2 NSFLS-1), interval singleton type-3 fuzzy logic systems (IT3 SFLS), and interval type-1 non-singleton type-3 fuzzy systems (IT3 NSFLS-1). The experiments show that the proposed EWH IT3 NSFLS-1 (OLS–BP) system presented superior capability to learn the knowledge and to predict the surface temperature with the lower prediction error. Full article

(1) Background: Patients with severe physical impairments (spinal cord injury, cerebral palsy, amyotrophic lateral sclerosis) often have limited mobility due to physical limitations, and may even be bedridden all day long, losing the ability to take care of themselves. In more severe cases, the ability to speak may even be lost, making even basic communication very difficult. (2) Methods: This research will design a set of image-assistive communication equipment based on artificial intelligence to solve communication problems of daily needs. Using artificial intelligence for facial positioning, and facial-motion-recognition-generated Morse code, and then translating it into readable characters or commands, it allows users to control computer software by themselves and communicate through wireless networks or a Bluetooth protocol to control environment peripherals. (3) Results: In this study, 23 human-typed data sets were subjected to recognition using fuzzy algorithms. The average recognition rates for expert-generated data and data input by individuals with disabilities were 99.83% and 98.6%, respectively. (4) Conclusions: Through this system, users can express their thoughts and needs through their facial movements, thereby improving their quality of life and having an independent living space. Moreover, the system can be used without touching external switches, greatly improving convenience and safety. Full article

The purpose of the present study is to propose an interval-valued type 2 fuzzy set (IT2FS)-based analytic hierarchy process (AHP) framework to unfold the critical challenging factors influencing the sustenance and growth of the Indian tea industry. The current work follows an expert opinion-based group decision-making approach. The challenging factors have been identified through a literature review and finalized after a pilot study based on the opinions of professionals, consumers, and experts. Finally, the critical challenging factors and sub-factors have been figured out through analysis of the responses of the experts. To offset the subjective bias, an IT2FS-based granular analysis has been carried out. The findings reveal that market diversification and productivity are the central issues. Additionally, it is important to give attention to improving the quality of the products, increasing the use of modern technology and organic farming, and developing a variety of products. The result shows a considerable level of consistency in the group decision-making (CR < 0.1) for all pairwise comparisons. The present work shall be of use to formulate appropriate strategies and policy decisions. It shows a robust application of IT2FS-AHP for complex decision-making in real life. Full article