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The purpose of this paper is to have a deeper understanding of the nonlinear relationship between the impact of climate change on tourism development. Current studies on the effects of climate change on tourism development primarily rely on linear correlation assumptions.

Based on the New Institutional Economics theory, the institutional setting inherently motivates and ensures the growth of the tourism industry. For a precise evaluation of the nonlinear consequences of climate change on tourism, this paper concentrates on Chinese cities between 2011 and 2021, methodically analyzing the influence of climate change on tourism.

The study findings suggest that there is an “inverse U”-shaped nonlinear relationship between climate change and tourism development, initially strengthening and subsequently weakening. Based on these findings, the research further delves into how institutional contexts shape the nonlinear association between climate change and tourism growth. It was found that in a higher institutional backdrop, the “inverse U” curve tends to flatten and surpass the curve adjusted for a lesser institutional context. Upon deeper mechanism analysis, it was observed that cities with more advanced marketization, improved industrial restructuring and enhanced educational growth exhibit a more evident “inverse U”-shaped nonlinear connection between climate change and tourism evolution.

First, previous studies on climate change and tourism development largely rely on questionnaire data (Hu et al., 2022). In contrast to these studies, this paper uses dynamic panel data, which to some extent overcomes the subjectivity and difficulty of causality identification in questionnaire data, making our research conclusions more accurate and reliable. Second, this study breaks through the linear relationship hypothesis of previous literature regarding climate change and tourism development. By evaluating the nonlinear relationship of climate change to tourism development from the institutional pressure perspective, it more intricately delineates their interplay mechanism, expanding and supplementing the research literature on the relationship mechanism between climate change and tourism development. Thirdly, the conclusions of this study are beneficial for policymakers to better understand and assess the scope of climate change impacts. It also aids relevant departments in clarifying the direction of institutional environment optimization to elevate the level of tourism development when faced with adverse impacts brought about by climate change.

A management summary of the theory and propositions with regard to the engineering of vision and culture in “corporate entities” is provided. It has been based on a book of the same title by the author, published in 1989 by Heinemann in the United Kingdom. In addition, a number of considerations and suggestions have been included in support of further research. The proposed diagnostic management model on organisational and possibly national dynamics emerged in a corporate rather than an “academic” campus. Its particular relevance therefore is both a reflection of an inductive reasoning process on corporate and national events, and of the practitioner′s need to cope with the continuous challenge of structural change.

Episodes of compulsive eating may lead to addiction. Changing relative prices does not always work for many food addicts turned overweight or obese individuals. This paper points to when such situations may arise and how they can be remedied.

We modify the standard neoclassical economics model assumption of indifference curves being convex to the origin. It becomes violated in situations when compulsive eaters become food addicts. As a result of that, the assumption of the concave (quasi-concave) utility function is violated too. We also introduce the possibility that compulsive eaters may have stable but nonconstant preferences.

Most important finding of our model is that a smooth dynamic path to addiction, caused by habit, disappears. Hence, the ability for smooth adjustment to relative price changes due to policies targeting obesity may not be applicable for a compulsive addict. We postulate the existence of thresholds past in which irreversible harm to addicted overeaters may occur. Reaching such states implies that no economic tools at our disposal could reverse the harm, which, in turn, deem that many policies directed at altering relative prices are ineffective in correcting overeating addiction and its consequences.

Even if we believe in consumer sovereignty, it is possible to shape consumer behavior via policy actions, including the behavior of extremum seekers turned addicts. The public policy of obesity should consider, in this case, its social cost.

No prior research has considered food addiction in light of compulsive eating caused by extremum-seeking behavior. Addiction correcting food policies always relied on either rational or myopic addiction models.

Addressing occupational stress and fostering employee wellness helps meet a host of organizational stakeholder expectations including high quality of work life (employees), reasonable return on investment (investors), increased productivity (management), and competitiveness (owners). Despite being dynamic in nature, stress and wellness are often studied using a static perspective. One reason for the scarcity of dynamic empirical research is the limited knowledge and use of the tools available to assess change over time. To address this limitation, four tools used to assess change and dynamics of occupational stress and well-being are described: growth models, latent change score models, spectral analysis, and computational modeling. First, we begin by discussing growth curve models and then transition to latent change score models. We then expand into spectral analysis, a tool used to determine cycles of ups and downs that repeat regularly. Last, computational modeling is discussed, where computers and simulations are used to understand a dynamic process. For each tool, we give examples of how they have been used, make recommendations for future use, and provide readers with suggestions and references for how to complete analyses in software and programs, most of which are freely available (i.e., R, Vensim).

This paper aims to propose a scenario-based approach for measuring interest rate risks. Many regulatory capital standards in banking and insurance make use of similar approaches. The authors provide a theoretical justification and extensive backtesting of our approach.

The authors theoretically derive a scenario-based value-at-risk for interest rate risks based on a principal component analysis. The authors calibrate their approach based on the Nelson–Siegel model, which is modified to account for lower bounds for interest rates. The authors backtest the model outcomes against historical yield curve changes for a large number of generated asset–liability portfolios. In addition, the authors backtest the scenario-based value-at-risk against the stochastic model.

The backtesting results of the adjusted Nelson–Siegel model (accounting for a lower bound) are similar to those of the traditional Nelson–Siegel model. The suitability of the scenario-based value-at-risk can be substantially improved by allowing for correlation parameters in the aggregation of the scenario outcomes. Implementing those parameters is straightforward with the replacement of Pearson correlations by value-at-risk-implied tail correlations in situations where risk factors are not elliptically distributed.

The paper assumes deterministic cash flow patterns. The authors discuss the applicability of their approach, e.g. for insurance companies.

The authors’ approach can be used to better communicate interest rate risks using scenarios. Discussing risk measurement results with decision makers can help to backtest stochastic-term structure models.

The authors’ adjustment of the Nelson–Siegel model to account for lower bounds makes the model more useful in the current low-yield environment when unjustifiably high negative interest rates need to be avoided. The proposed scenario-based value-at-risk allows for a pragmatic measurement of interest rate risks, which nevertheless closely approximates the value-at-risk according to the stochastic model.

This article identifies serious weaknesses in various commonly used methods of measuring “average” growth rates over several time periods. An alternative method is proposed which satisfies two essential criteria: firstly it smoothes the data to remove “exceptional variation” in the time series, and secondly, it incorporates a compounding process which, it is suggested, is an essential requirement of a “correct” average growth rate.

To develop a new method for computer‐based 3D construction of garment basic cut on a computer generated body model.

The method has been developed on an example of a 3D garment basic cut construction on a virtual body model, determining the position of characteristic 3D points necessary for computer‐based definition of 3D cutting pattern contour segments. Contour segments modelling, as well as the modelling of 3D cut surfaces has been done using the NURBS objects.

A 3D garment cut has been constructed, such that matches physical characteristics of the body in question and offers the necessary comfort of the cut. The surface of the 3D cut has been divided into individual 3D cutting patterns.

The method has been developed on an example of a 3D garment basic cut construction of a single paper of clothing. However, the same principles can be applied and developed for any garment basic cut.

The 3D garment cut constructed can be further transformed into a network of polygons. Introducing fabric physical‐chemical properties fabric drape can be simulated, aiming at more realistic visualisation and further assessment of the garment fit. The 3D cutting patterns developed can be, applying computer‐based application of the mathematical models, transformed into 2D cutting patterns.

As compared to the methods developed by some previous investigations, the newly developed method offers the construction of garment 3D cut on a computer‐generated body model, granting the necessary comfort of the cut, which also means garment fitted to individual body characteristics. The 3D cut constructed can also be used as a starting point to define 2D cutting patterns in the following step, which will be matched to the physical characteristics of the model body, in the same way as the initial 3D cut.

The aim of this paper is to investigate implementations of carbon‐black filled silicone rubber for tactile sensation.

The sensor‐elements for this tactile sensing structure were made by press‐curing from carbon‐black filled silicone rubber.

The behaviour of the silicone rubber shows strong non‐linearity, therefore, the sensor cannot be used for accurate measurements. The greatest advantage of this material lies in its high elasticity.

A new method for artificial tactile sensing skin for robotic applications.

The purpose of this paper is to propose a new approach for designing different parts of a high voltage bushing. It also aims to consider technical and economical criteria for the optimum solution of the design problem.

A novel method for finding the optimal contours of different elements of high voltage bushings, including ceramic insulator, electrode, and flange angle is presented. The rational Bézier curves are used for defining the surface of the insulators and conductors of the equipment. Then, these curves are optimally adjusted to obtain an appropriate techno‐economical solution. The utilized optimization method is the improved bacterial foraging algorithm (BFA) with variable step sizes. In the design procedure, two‐dimensional finite element method (2D FEM) is used to calculate the performance parameters in each step of the design procedure. In order to evaluate the performance of the proposed algorithm, optimal design of different elements of a 110 kV bushing using BFA and genetic algorithm is presented, compared, and discussed as well.

The results of this research show that the technical design criteria and economical costs are satisfied by the proposed method. It is concluded that the rational Bézier curves can be implemented for other similar applications and optimal design of other equipment in the electrical engineering field combined with heuristic optimization techniques.

Bezier curves are used for the first time for bushing design purpose. Two heuristic techniques are also implemented in order to facilitate the comparison and avoid local solutions.