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The cultural tourism industry, which has subtly met the needs and solved the major problem of the current age, is a new growth point for the current city economic growth. Therefore, its position in the industrial structure system will be increasingly improved. The development of the cultural tourism industry also provides an important opportunity for the renewal and re-engineering of urban space. For the current urban space construction crisis needs the integration of historical and cultural elements urgently while the development of the cultural tourism industry itself happened to need the city to provide the necessary carrying space and incubation carrier urgently as well. Thus this research discusses the construction of urban visual planning system and the specific implementation path from the perspective of the development of cultural tourism industry.

The purpose of this paper is to introduce an improved system identification method for small unmanned helicopters combining adaptive ant colony optimization algorithm and Levy’s method and to solve the problem of low model prediction accuracy caused by low-frequency domain curve fitting in the small unmanned helicopter frequency domain parameter identification method.

This method uses the Levy method to obtain the initial parameters of the fitting model, uses the global optimization characteristics of the adaptive ant colony algorithm and the advantages of avoiding the “premature” phenomenon to optimize the initial parameters and finally obtains a small unmanned helicopter through computational optimization Kinetic models under lateral channel and longitudinal channel.

The algorithm is verified by flight test data. The verification results show that the established dynamic model has high identification accuracy and can accurately reflect the dynamic characteristics of small unmanned helicopter flight.

This paper presents a novel and improved frequency domain identification method for small unmanned helicopters. Compared with the conventional method, this method improves the identification accuracy and reduces the identification error.

The purpose of this paper is to investigate the influence of two dimensions of relational risks, namely, opportunism behavior and interest conflict, on knowledge flow and to explore the moderating effect of network power among these untested relationships and to examine the positive effect of opportunism behavior and interest conflict.

This paper adopts survey data collected from 180 enterprises in China's high-technology industry and examines the relationship between relational risks, network power and knowledge flow.

This research empirically shows that opportunism behavior and interest conflict significantly and negatively impact on knowledge flow. Those relationships are positively moderated by network power.

To be more generalized to the high-technology industry, future research should adopt the quantitative research, which can obtain more comprehensive information to explore the nature of phenomenon. The future research can also combine with other variables. In addition, this research extends the current literature by investigating the relationship of so far understudied theorized antecedents.

This research enriches the related network perspective literature by providing new insight combining relational risks and knowledge flow. Especially, the moderating effect of network power is empirically examined.

The paper attempts to establish a two‐dimension frame to analyze dynamic supplier risks of large‐scale and complex equipment and study the probability distribution of the occurring risks.

Starting from the dynamic and correlated supplier risks of large‐scale and complex equipment, a two‐dimension frame to analyze these risks is established. A maximum entropy model is also built to research the probability distribution of the risks; then, K‐T conditions are proved to solve the model. A real case is also studied in the last part of the paper.

The results are convincing: in order to analyze the supplier risk dynamically of large‐scale and complex equipment development project, a two‐dimension analysis frame is established and a maximum entropy model is worked out. The case study shows that they are valuable.

The two‐dimension frame gives a new viewpoint for risk management, but also the maximum entropy model supplies a valuable method for risk management.

The paper succeeds in creating a dynamic analysis frame to study risks and building a new method to research the disciplines of the dynamic risks.

With rapid urbanization, cities are facing various ecological and environmental problems. Living in harmony with nature is more important than ever. This paper aims to evaluate the ecosystem and ecological features of Azheke village, a key component of the Hani Rice Terraces World Cultural Heritage in China. The focus is on exploring effective ways to improve the relationship between humans and the natural environment through urban design in order to create a livable and sustainable city that can promote the development of sustainable smart urban ecology design.

This study conducted a systematic literature review to answer the following research questions: (1) How does Azheke design achieve harmony between humans and nature? (2) What are the effective approaches to improve the relationship between humans and nature within urban ecosystems? (3) How can urban design learn and integrate from Azheke’s ecological features to improve the relationship between humans and nature?

Azheke sustains long-term human-nature harmony through traditional ecological knowledge (TEK) and efficient natural resource use. By incorporating biophilic design and nature-based solutions from Azheke, along with biodiversity-friendly urban planning, we can boost urban ecosystem health and create unique Azheke-inspired urban designs.

This research primarily focuses on the human-nature relationship, exploring design strategies based on biodiversity without delving into the interactions between other components of urban ecosystems, such as social-cultural and economic components.

This paper provides a new perspective and strategies for developing sustainable and smart urban ecology design. These findings can provide theoretical references for urban planners, designers and decision-makers.

Agriculture and cultivation firms are facing severe competition in the saturated market. Due to the characteristics of heavy assets, low investment return, long cycle and high price fluctuation, agri-food firms require innovations for capital support. The purpose of this paper is to provide valuable insights on how firms in the food/agricultural industry approach innovations and reinforce their advantages through functional and structural innovations by adopting supply chain finance (SCF).

This research adopts a single-case study methodology to investigate the innovations and mechanisms taking place at H Corp Agriculture Group (H Corp hereafter), a Chinese egg company.

The findings of this paper indicate that SCF could have a great impact on supply chain management through functional and structural innovations throughout the supply chain and solve the capital constraint problems in the agricultural development process, promoting the implementation of the integration strategy as well as innovation in the agricultural industry chain. The research also shows that supply chain structural and functional innovations could promote corporate social responsibility (CSR) and creating shared value (CSV).

The research contributes to the application of SCF mechanisms and the realization of CSV and CSR jointly – both in the literature and in firms’ practices. It also contributes to the extension of structural and functional innovations and vertical integration of the supply chain. However, generalizability and universality are insufficient for a single case study in the specified industry. Data collection and quantitative analysis could be extended for further research.

The study addresses the need for comprehensive research on SCF and its applications. It proposes effective and efficient strategies for agri-food firms applying SCF to overcome industry capital constraints and develop competitiveness. It also provides a balanced and positive circulation between economic value and social value, realizing CSR and CSV.

The study aimed to outlay the substantial relationship to information and studies on sustainable tourism, environmental sustainability and local resource governance issues. It further contextualizes the essence of natural biodiversity, ecotourism and residents integrated subsistence. Meanwhile, delving into the community’s sustainability and climate change perceptions within the Vhembe district of Limpopo Province of South Africa’s Musina Municipality.

The municipality’s circumstances for managing its natural and tourism resources were investigated through a general review of the literature, document reviews, focus groups and field observations. The data analysis procedure was finished with manual sorting, central tendencies and frequency distribution.

It was discovered that there is a negative correlation between activities that have the potential to contribute to climate change and the environmental consequences of rural ecotourism. Sustainable ecotourism management can lead to sustainability accomplishments when tourism activities follow the principles of ethical and sustainable travel, enhancing public leadership and livelihood values.

The possible and present effects of ecotourism and integrated rural livelihoods on local communities, pertaining to sustainability and climate change, are brought forth with notions for significant enhancement measures for social sustainability.

Within the municipality, the study compares ecotourism, conservation and environmental degradation in terms of sustainability, responsible tourism and sustainable tourism. Moving forward, the essence of tourism-based public leadership within the context of community-based natural resources management and community-based tourism that supports integrated livelihoods and strategies for environmental sustainability is highlighted and can be enhanced by the endorsement of various technologies within the emerging economies.

This study aims to present the climate change effect on potential evapotranspiration (ETP) in future periods.

Daily minimum and maximum temperature, solar radiation and precipitation weather parameters have been downscaled by global circulation model (GCM) and Lars-WG outputs. Weather data have been estimated according to the Had-CM3 GCM and by A1B, A2 and B1 scenarios in three periods: 2011-2030, 2045-2046 and 2080-2099. To select the more suitable method for ETP estimation, the Hargreaves-Samani (H-S) method and the Priestly–Taylor (P-T) method have been compared with the Penman-Monteith (P-M) method. Regarding the fact that the H-S method has been in better accordance with the P-M method, ETP in future periods has been estimated by this method for different scenarios.

In all five stations, in all three scenarios and in all three periods, ETP will increase. The highest ETP increase will occur in the A1B scenario and then in the A1 scenario. The lowest increase will occur in the B1 scenario. In the 2020 decade, the highest ETP increase in three scenarios will occur in Khorramabad and then Hamedan. Kermanshah, Sanandaj and Ilam stations come at third to fifth place, respectively, with a close increase in amount. In the 2050 decade, ETP increase percentages in all scenarios are close to each other in all the five stations. In the 2080 decade, ETP increase percentages in all scenarios will be close to each other in four stations, namely, Kermanshah, Sanandaj, Khorramabad and Hamedan, and Ilam station will have a higher increase compared with the other four stations.

Meanwhile, the highest ETP increase will occur in hot months of the year, which are significant with regard to irrigation and water resources.

Considering the influence of environmental noise and modeling error during the process of the robotic automatic grinding aero-engine blade, this study aims to propose a method based on the extended state observer (ESO) to reduce the fluctuation of normal grinding force.

First, the measurement range of the six-dimensional force sensor is calibrated according to the maximum acceleration of end-effector and grinding force. Second, the gravity and zero drift compensation model is built to compensate for measurement error. Finally, the switching function is designed based on the difference between the expected grinding force and the actual feedback value. When the value of function stays within the switching band, a nonlinear active disturbance rejection control (ADRC) loop is applied. When the function value reaches outside the switching band, an ESO-based sliding mode control (SMC) loop is applied.

The simulated and experimental results show that the proposed control method has higher robustness compared with proportion-integral-derivative (PID), Fuzzy PID and ADRC.

The processing parameters of this paper are obtained based on the single-factor experiment without considering the correlation between these variables. A new control strategy is proposed, which is not only used to control the grinding force of blades but also promotes the development of industrial control.

ESO is used to observe environmental interference and modeling errors of the system for real-time compensation. The segment control method consisting of ESO-based SMC and ESO-based ADRC is designed to improve the robustness. The common application of the two parts realizes suppression of fluctuation of grinding force.

The connection between digital manufacturing technologies (Industry 4.0) and the environment has sparked discussions on firms' disclosure of negative information on pollutant emissions and the pursuit of positive environmental outcomes. However, very few studies explore how it relates to a firm's robot usage and its mechanism. The purpose of this paper is to investigate the impacts of robot penetration on firms' environmental governance in China.

The ordered probit model (and probit model) are employed and empirically tested with a sample of 1,579 Chinese listed firms from 2010 to 2019.

The study reveals a negative relationship between robot usage and the disclosure of negative indicators and a U-shaped relationship between robot usage and positive environmental outcomes. Among the sample, nonstate-owned enterprises (SOEs) display unsatisfactory performance, while heavily polluting industries disclose more information on pollutant emissions. The robot–environmental governance nexus is conditional on firm size, capital intensity and local economic development.

The study proposes a fresh view of corporate environmental governance to assess the environmental implications of robot adoption. It also contributes to identifying the curvilinear, moderating and heterogenous effects in the robot–environment nexus. The results provide rich policy implications for the development of industrial intelligence and corporate environmental governance in the circular economy (CE) context.