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Economic incentives, government regulations, and customer perspective on environmental consciousness (EC) are driving more and more companies into product recovery business, which forms the basis for a reverse supply chain. A reverse supply chain consists a series of activities that involves retrieving used products from consumers and remanufacturing (closed-loop) or recycling (open-loop) them to recover their leftover market value. Much work has been done in the areas of designing forward and reverse supply chains; however, not many models deal with the transshipment of products in multiperiods. Linear physical programming (LPP) is a newly developed method whose most significant advantage is that it allows a decision-maker to express his/her preferences for values of criteria for decision-making in terms of ranges of different degrees of desirability but not in traditional form of weights as in techniques such as analytic hierarchy process, which is criticized for its unbalanced scale of judgment and failure to precisely handle the inherent uncertainty and vagueness in carrying out pair-wise comparisons. In this chapter, two multiperiod models are proposed for a remanufacturing system, which is an element of a Reverse Supply Chain (RSC), and illustrated with numerical examples. The first model is solved using mixed integer linear programming (MILP), while the second model is solved using linear physical programming. The proposed models deliver the optimal transportation quantities of remanufactured products for N-periods within the reverse supply chain.

This chapter analyzes the attribute associations, supplied by experts, of top 10 destination brands in Spain. Using a sample of respondents that represents the domestic tourist population, the study examined how they perceive the importance of each of the attributes when selecting a holiday destination. They are rated for all the 10 brands as a whole and for each individually. Comparisons are made between each and the average of all other brands. The application of multidimensional scale method resulted in five distinct groups or competitive sets based on the similarities and disparities of tourists’ ratings of these attributes. For each, the study suggests how these sets are perceived as a whole and in comparison with each other. The chapter offers meaningful relationships between the respondents’ demographic and socioeconomic characteristics and their perceived importance of the destination brands’ attributes.

The main aim of the current paper is to find a numerical plan for hydraulic fracturing problem with application in extracting natural gases and oil.

First, time discretization is accomplished via Crank-Nicolson and semi-implicit techniques. At the second step, a high-order finite element method using quadratic triangular elements is proposed to derive the spatial discretization. The efficiency and time consuming of both obtained schemes will be investigated. In addition to the popular uniform mesh refinement strategy, an adaptive mesh refinement strategy will be employed to reduce computational costs.

Numerical results show a good agreement between the two schemes as well as the efficiency of the employed techniques to capture acceptable patterns of the model. In central single-crack mode, the experimental results demonstrate that maximal values of displacements in x- and y- directions are 0.1 and 0.08, respectively. They occur around both ends of the line and sides directly next to the line where pressure takes impact. Moreover, the pressure of injected fluid almost gained its initial value, i.e. 3,000 inside and close to the notch. Further, the results for non-central single-crack mode and bifurcated crack mode are depicted. In central single-crack mode and square computational area with a uniform mesh, computational times corresponding to the numerical schemes based on the high order finite element method for spatial discretization and Crank-Nicolson as well as semi-implicit techniques for temporal discretizations are 207.19s and 97.47s, respectively, with 2,048 elements, final time T = 0.2 and time step size τ = 0.01. Also, the simulations effectively illustrate a further decrease in computational time when the method is equipped with an adaptive mesh refinement strategy. The computational cost is reduced to 4.23s when the governed model is solved with the numerical scheme based on the adaptive high order finite element method and semi-implicit technique for spatial and temporal discretizations, respectively. Similarly, in other samples, the reduction of computational cost has been shown.

This is the first time that the high-order finite element method is employed to solve the model investigated in the current paper.

Visual feedback control is a promising solution for robots work in unstructured environments, and this is accomplished by estimation of the time derivative relationship between the image features and the robot moving. While some of the drawbacks associated with most visual servoing (VS) approaches include the vision–motor mapping computation and the robots’ dynamic performance, the problem of designing optimal and more effective VS systems still remains challenging. Thus, the purpose of this paper is to propose and evaluate the VS method for robots in an unstructured environment.

This paper presents a new model-free VS control of a robotic manipulator, for which an adaptive estimator aid by network learning is proposed using online estimation of the vision–motor mapping relationship in an environment without the knowledge of statistical noise. Based on the adaptive estimator, a model-free VS schema was constructed by introducing an active disturbance rejection control (ADRC). In our schema, the VS system was designed independently of the robot kinematic model.

The various simulations and experiments were conducted to verify the proposed approach by using an eye-in-hand robot manipulator without calibration and vision depth information, which can improve the autonomous maneuverability of the robot and also allow the robot to adapt its motion according to the image feature changes in real time. In the current method, the image feature trajectory was stable in the camera field range, and the robot’s end motion trajectory did not exhibit shock retreat. The results showed that the steady-state errors of image features was within 19.74 pixels, the robot positioning was stable within 1.53 mm and 0.0373 rad and the convergence rate of the control system was less than 7.21 s in real grasping tasks.

Compared with traditional Kalman filtering for image-based VS and position-based VS methods, this paper adopts the model-free VS method based on the adaptive mapping estimator combination with the ADRC controller, which is effective for improving the dynamic performance of robot systems. The proposed model-free VS schema is suitable for robots’ grasping manipulation in unstructured environments.

The aim of this study was to investigate consumer preferences and profile their food-related lifestyles, as well as to identify consumer groups with similar attitudes/behaviours in the Euro-Mediterranean fruit and vegetable market.

A structured questionnaire was designed drawing from the food related lifestyles instrument and including other factors relevant to fruit and vegetable consumer preferences. The data were collected in an online survey with 925 participants in France, Greece, and Italy. A principal component analysis was conducted to interpret and examine consumers' fruit and vegetable related lifestyles. In addition, a cluster analysis was performed to identify different consumer segments, based on the core dimensions of the food-related lifestyle approach.

In each country, three primary consumer segments were distinguished. Health-conscious individuals were predominant in France and Greece, while quality-conscious consumers were prevalent in Italy. These classifications were determined considering various factors such as purchase motivation, perception of product quality, health concerns, environmental certifications, and price sensitivity.

The food-related lifestyle approach has been adapted instrument to create a customised survey instrument specifically designed to capture the intricacies of fruit and vegetable consumer preferences and priorities in three Euro-Mediterranean Countries.

This study aims to investigate how sensory cue order, wine knowledge and visual–olfactory (V–O) congruence affect consumer’s taste perceptions of wine and their subsequent behavior.

An experiment was performed to identify the effects of sensory cue congruence and sensory cue order on wine consumers’ perceptions of wine, affective evaluations, cognitive evaluations and purchase intentions.

Wine experts exhibited positive emotional responses to congruent sensory cues in the V–O order. Experts’ enjoyment of wine’s aroma, their emotional responses, their cognitive evaluations and their purchase intentions were lower in the incongruent condition. Consumers’ negative emotions elicited by the V–O sequence were also less intense than those triggered by the olfactory–visual (O–V) sequence. Wine experts demonstrated more positive emotional responses in the V–O sensory congruent condition.

This study highlights how visual and olfactory sensory cue order, wine knowledge and sensory cue congruence interact to clarify wine-related behavioral intention. Findings reveal the roles of these factors in shaping sensory perceptions, cognitive evaluations, affective evaluations and behavior related to wine consumption.

This study holds implications for various stakeholders, including winemakers, wine businesses, restaurants and the broader hospitality industry. Wine businesses can enhance advertising effectiveness by tailoring their marketing efforts to customers’ knowledge levels and emphasizing the inherent attributes that align with individuals’ preferences. Winemakers can improve consumers’ sensory experiences by enhancing the natural color of wines. Restaurants can strive to ignite diners’ positive emotions and experiences by providing congruent information. Furthermore, sensory-driven strategies can be used in the hospitality sector to elevate customers’ positive emotions.

This study fills gaps in wine research by delineating how wine knowledge and related sensory cues can influence consumers’ sensory perceptions, cognitive evaluations, affective evaluations and behavior. These aspects have been largely overlooked in previous work.

Based on previous results of the existence, uniqueness, and regularity conditions for a continuous dynamic model for a parallel-plate electrostatic micro-electron-mechanical-systems with the fringing field, the purpose of this paper concerns a Galerkin-FEM procedure for deformable element deflection recovery. The deflection profiles are reconstructed by assigning the dielectric properties of the moving element. Furthermore, the device’s use conditions and the deformable element’s mechanical stresses are presented and discussed.

The Galerkin-FEM approach is based on weighted residuals, where the integrals appearing in the solution equation have been solved using the Crank–Nicolson algorithm.

Based on the connection between the fringing field and the electrostatic force, the proposed approach reconstructs the deflection of the deformable element, satisfying the conditions of existence, uniqueness and regularity. The influence of the electromechanical properties of the deformable plate on the method has also been considered and evaluated.

The developed analytical model focused on a rectangular geometry.

The device studied is suitable for industrial and biomedical applications.

This paper proposed numerical approach characterized by low CPU time enables the creation of virtual prototypes that can be analyzed with significant cost reduction and increased productivity.

This paper originally proposed the fuzzy option pricing method for green bonds. Based on the requirements of arbitrage equilibrium, this paper draws on Merton's corporate bond option pricing model.

Describing the asset value behavior of green bond issuing enterprises through diffusion-jump processes to reflect the uncertainty brought by carbon emission reduction policies and technologies, using approximation methods to get the analytical pricing formula and then, using a fuzzification technique of Choquet expectation under  λ-additive fuzzy measures after considering fuzzy factors, the paper provides fuzzy intervals for the parity coupon rates of green bonds with different subjective levels for investors.

The paper proposes and argues the classical and fuzzy option pricing methods in turn for both corporate ordinary bonds and green bonds, considering carbon risk or climate risk. It implements the scenario analysis varying with industry emission standards and discusses the sensitiveness of the related key parameters of the option.

The fuzzy option pricing for the green bonds provides the scope of the variable equilibrium values, operational theoretical supports and some policy implications of carbon reduction and promoting green funding.

The logic of introducing the fuzziness of the option pricing for the green bonds lies with considering the existence of fuzzy information about the project supported by the green bond and the subjectivity of investors and it also responds to changes in technological uncertainty and policy uncertainty in the process of “carbon peaking and carbon neutrality.”