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The paper examines how local governments’ responses to citizens’ complaints about environment issues are affected when the complaints involve conflicting goals, particularly economic versus environmental goals. This study focuses on the responsiveness of provincial governments to citizen environmental complaints on the Local Leader Message Board (LLMB) in China.

This study collected 125,364 environment-related complaints lodged by citizens on the LLMB from 2013 to 2021 and identified complaints embodying conflicting goals through a Structural Topic Model (STM). Advanced supervised machine learning (ML) algorithms were employed to enhance the robustness of the findings.

The results indicate that provincial governments prioritize citizens’ complaints across different types of issues. However, complaints embodying conflicting goals (related to environmental issues) are less likely to get a response. This relationship is moderated by an inverted U-shaped effect of economic dependence on industries. This suggests that the impact of conflicting goals on government responsiveness is dynamic, with the likelihood of provincial governments responding to conflicting complaints initially increasing and then decreasing as economic dependence on industries rises.

The findings enrich the understanding of the consequences of conflicting goals by highlighting their potential as a mechanism to explain the strategic reactions of governments to citizens.

The purpose of this paper is to develop a methodology for the stochastically asymptotic synchronization problem for a class of neutral-type chaotic neural networks with both leakage delay and Markovian jumping parameters under impulsive perturbations.

The authors perform drive-response concept and time-delay feedback control techniques to investigate a class of neutral-type chaotic neural networks with both leakage delay and Markovian jumping parameters under impulsive perturbations. New sufficient criterion is established without strict conditions imposed on the activation functions.

It turns out that the approach results in new sufficient criterion easy to be verified but without the usual assumption of the differentiability and monotonicity of the activation functions. Two examples show the effectiveness of the obtained results.

The novelty of the proposed approach lies in removing the usual assumption of the differentiability and monotonicity of the activation functions, and the use of the Lyapunov functional method, Jensen integral inequality, a novel Gu’s lemma, reciprocal convex and linear convex combination technique for the stochastically asymptotic synchronization problem for a class of neutral-type chaotic neural networks with both leakage delay and Markovian jumping parameters under impulsive perturbations.

The purpose of this paper is to develop a methodology for the stochastically asymptotic stability of fuzzy Markovian jumping neural networks with time-varying delay and continuously distributed delay in mean square.

The authors perform Briat Lemma, multiple integral approach and linear convex combination technique to investigate a class of fuzzy Markovian jumping neural networks with time-varying delay and continuously distributed delay. New sufficient criterion is established by linear matrix inequalities conditions.

It turns out that the obtained methods are easy to be verified and result in less conservative conditions than the existing literature. Two examples show the effectiveness of the proposed results.

The novelty of the proposed approach lies in establishing a new Wirtinger-based integral inequality and the use of the Lyapunov functional method, Briat Lemma, multiple integral approach and linear convex combination technique for stochastically asymptotic stability of fuzzy Markovian jumping neural networks with time-varying delay and continuously distributed delay in mean square.

The purpose of this paper is to develop a method for the existence, uniqueness and globally robust stability of the equilibrium point for Cohen–Grossberg neural networks with time-varying delays, continuous distributed delays and a kind of discontinuous activation functions.

Based on the Leray–Schauder alternative theorem and chain rule, by using a novel integral inequality dealing with monotone non-decreasing function, the authors obtain a delay-dependent sufficient condition with less conservativeness for robust stability of considered neural networks.

It turns out that the authors’ delay-dependent sufficient condition can be formed in terms of linear matrix inequalities conditions. Two examples show the effectiveness of the obtained results.

The novelty of the proposed approach lies in dealing with a new kind of discontinuous activation functions by using the Leray–Schauder alternative theorem, chain rule and a novel integral inequality on monotone non-decreasing function.

Purpose: Industry 5.0 is characterized by a revolution in the industrial field where humans collaborate with machines. This study aims to highlight the role of the concept of the “Digital Twin” (DT) within Industry 5.0, aiming to predict the effects of natural disaster scenarios in advance and to take preventive measures more effectively.

Need for the study: The innovations brought by Industry 5.0 demonstrate the possibility of creating DTs of cities to predict and minimize the effects of natural disasters. This is of great importance in terms of preparation for future natural disasters and risk management.

Methodology: This study was conducted by analyzing the fundamental principles of Industry 5.0 and the concept of DTs. Scientific literature and industry reports were examined to explore how DTs can be used in the field of risk management related to natural disasters.

Findings: The use of DTs has significant potential in simulating natural disaster scenarios in advance and predicting potential damages. For example, through DTs of cities, the effects of disaster scenarios such as earthquakes, tsunamis, and floods can be analyzed in advance, and necessary measures can be taken accordingly.

Practical implications: These findings offer important practical implications for decision-makers working in areas such as urban planning and infrastructure management. The use of DTs can assist in the development of preparation and risk management strategies for natural disasters, thereby minimizing the impact of disasters and ensuring the safety of individuals.

It has been witnessed that many incidents of crowd evacuation have resulted in catastrophic results, claiming lives of hundreds of people. Most of these incidents were a result of localized herding that eventually turned into global panic. Many crowd evacuation models have been proposed with different aspects of interests. The purpose of this paper is to attempt to bring together many of these aspects to study evacuation dynamics.

The proposed agent-based model, in a hypothetical physical environment, uses perception maps for routing decisions which are constructed from agents’ personal observations of the surroundings as well as information gathered through distant communication. Communication is governed by a trust model which measures the authenticity of the information being shared. Agents are of two types; emotional and rational. The trust model is combined with a game-theoretic model to resolve conflict of agents’ own type with that of types of agents in the neighborhood.

Evacuation dynamics in different environmental and exit strategies are evaluated on the basis of reduced herding and evacuation time. Using this integrated information sharing model, agents gain an overall view of the environment, sufficient to select the optimal path towards exits with respect to reduced herding and evacuation time.

The proposed model has been formulated and established using an agent-based simulation integrating important modeling aspects. The paper helps in understanding the interplay between technological and humanistic aspects in smart and pervasive environments.

This chapter explores the role of artificial intelligence (AI), particularly its subfield of machine learning (ML) methods, as a core technology of the fintech revolution in the financial services industry. It simplifies some of the complex concepts related to AI by introducing the main ML paradigms and related techno-methodic aspects. This chapter uses real-world examples to illustrate how next-generation AI powered by ML is transforming the financial services industry. Next, in illustrating the risks associated with AI adoption, this chapter discusses the need for regulation to address the essential facets of AI governance, including transparency, accountability, ethics, and responsible use. Lastly, it looks at emerging regulatory approaches across leading global jurisdictions. The primary goal is to give readers an initial understanding of AI's profound impact on the financial sector.

Since the beginning of 2020, COVID-19 has dictated to the world what can be done or not. Log downs of countries, cities and businesses dominated the daily life of everybody. Especially the hospitality and tourism industry went through constant changes in rules and regulations. Tourists were not sure if they were allowed to travel or have to cancel their vacations. Hotels needed to be aware of COVID-19 registration and hygiene. In China, the Zero-COVID policies were wicked, strict and specific and should support daily businesses in the country. A specially used instrument was the variety of QR codes in place to prevent virus outbreaks and monitored tourism movements. For example, the city health QR code of each city/region in China, or the travel QR code to ensure safe travel. This chapter firstly looking into the ideas and policies behind the QR code system in China and secondly discovers through examples its efficiency. The final step is to propose a universal strategy on how QR codes and their policies can support safe and healthy hospitality and tourism recovery during the current pandemic crisis and protect tourists and the hospitality and tourism industry in future pandemic situations.

This paper aims to provide a posture generation method of robot deposition paths based on intersection topology, which is helpful to contribute to improving the flexibility and deposition capability of the deposition system.

Via the geometry information and normal vector information of the stereolithography (STL) model, the intersecting edge information is generated and the topological relationship of the model is established. Through the removal of redundant points for the STL model and the sort of robot path points, the position information of robot path points is obtained. According to the geometric relationship between the normal vector information of the STL model and the robot deposition path points, combining with the robot posture representation method of roll-pitch-yaw angles, the posture information of path points is achieved. Then, the generation from CAD model of parts to robot paths for laser melting is realized, and the experimental verification is carried out.

For simple parts, the laser melting process can be completed without the posture information of deposition paths. However, in the melting process of a turbine blade, there are some accumulated burls on the sidewall. The posture generation method of robot deposition paths based on the intersection topology can solve this problem. The light spot of deposition points irradiates on the surface of the forming part, and the forming process can proceed smoothly.

As a motion platform in laser melting deposition (LMD), the application of the multi-joint robot can improve the flexibility and deposition capability of the deposition system, as well as promote the LMD application for individuation manufacturing, parts repair and green remanufacturing.

The posture is essential for robot deposition paths. This paper first proposes a posture generation method of deposition paths for LMD to improve the flexibility and deposition capability of LMD systems.

In an integrated circuit (IC) substrate, more fillers, including talcum powder and aluminium hydroxide, are added, which leads to much higher rigidity and hardness compared with a traditional printed circuit board. However, the micro drilling of IC substrates is harder. This paper aims to test the drilling process of IC substrates to improve the drilling process and the micro hole quality.

Substrate drilling by a micro drill with 0.11-mm diameter was used under several drilling conditions. The influence of drilling conditions on the drilling process was observed. Drilling forces, drill wear and micro hole quality were also studied.

The deformation circle around holes, hole location accuracy, bugle hole and burrs were the major defects of micro holes that were observed during the drilling of the substrate. Reducing the drilling force and drill wear was the effective way to improve hole quality.

The technology and manufacturing of IC substrates has been little investigated. Research data on drilling IC substrates is lacking. The micro hole quality directly affects the reliability of IC substrates. Thus, improving the drilling technology of IC substrates is very important.