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With the development of artificial intelligence, proximity sensors show their great potential in intelligent perception. This paper aims to propose a new planar capacitive sensor for the proximity sensing of a conductor.

Different from traditional structures, the proposed sensor is characterized by sawtooth-structured electrodes. A series of numerical simulations have been carried out to study the impact of different geometrical parameters such as the width of the main trunk, the width of the sawtooth and the number of sawtooths. In addition, the impact of the lateral offset of the approaching graphite block is investigated.

It is found that sensitivity is improved with the increase of the main trunk with, sawtooth width and sawtooth number while a larger lateral offset leads to a decrease in sensitivity. The performance of the proposed planar capacitive proximity sensor is also compared with two conventional planar capacitive sensors. The results show that the proposed planar capacitive sensor is obviously more sensitive than the two conventional planar capacitive sensors.

In this paper, a new planar capacitive sensor is proposed for the proximity sensing of a conductor. The results show that the capacitive sensor with the novel structure is obviously more sensitive than the traditional structures in the detection of the proximity conductor.

Disruptions at ports may destroy the planned ship schedules profoundly, which is an imperative operation problem that shipping companies need to overcome. This paper attempts to help shipping companies cope with port disruptions through recovery scheduling.

This paper studies the ship coping strategies for the port disruptions caused by severe weather. A novel mixed-integer nonlinear programming model is proposed to solve the ship schedule recovery problem (SSRP). A distributionally robust mean conditional value-at-risk (CVaR) optimization model was constructed to handle the SSRP with port disruption uncertainties, for which we derive tractable counterparts under the polyhedral ambiguity sets.

The results show that the size of ambiguity set, confidence level and risk-aversion parameter can significantly affect the optimal values, decision-makers should choose a reasonable parameter combination. Besides, sailing speed adjustment and handling rate adjustment are effective strategies in SSRP but may not be sufficient to recover the schedule; therefore, port skipping and swapping are necessary when multiple or longer disruptions occur at ports.

Since the port disruption is difficult to forecast, we attempt to take the uncertainties into account to achieve more meaningful results. To the best of our knowledge, there is barely a research study focusing on the uncertain port disruptions in the SSRP. Moreover, this is the first paper that applies distributionally robust optimization (DRO) to deal with uncertain port disruptions through the equivalent counterpart of DRO with polyhedral ambiguity set, in which a robust mean-CVaR optimization formulation is adopted as the objective function for a trade-off between the expected total costs and the risk.

The purpose of this study is to identify the process of virtual influencer stickiness in the age of influencer marketing, which has received little attention in the literature. This is essential because the research creates a theoretical model of follower loyalty/stickiness to virtual influencer techniques from the standpoint of influencer marketing, which has a substantial effect on the evolution of the global marketing world.

In 2022, 302 people who currently follow an Instafamous virtual influencer took part in an Instagram self-administered online survey.

The findings show that both expertise and trustworthiness have a positive and significant influence on parasocial interaction, which in turn has a significant influence on virtual engagement and stickiness.

This research will specifically assist international readers in understanding how to harness and increase the efficiency and efficacy of interactive marketing strategies and methods to engage and retain followers of Instafamous virtual influencer. Moreover, the findings will be beneficial to opinion leaders, brand managers, company investors, entrepreneurs and service designers.

1. The study pioneers a holistic virtual follower stickiness mechanism that comprises the role of source credibility, parasocial interaction, informational influence and virtual follower’s engagement and their interrelationship to each other.

2. This study is based on parasocial interaction theory and source credibility theory to understand the relationship between virtual followers and influencers stickiness process at social media platforms.

3. In addition, the study examined the subsequent effects of sources of credibility components on parasocial interaction; as well as, on virtual follower engagement and stickiness.

4. This study also categorized and examined the moderating effects exerted by the genres of informative influence of virtual influencer.

The study pioneers a holistic virtual follower stickiness mechanism that comprises the role of source credibility, parasocial interaction, informational influence and virtual follower’s engagement and their interrelationship to each other.

This study is based on parasocial interaction theory and source credibility theory to understand the relationship between virtual followers and influencers stickiness process at social media platforms.

In addition, the study examined the subsequent effects of sources of credibility components on parasocial interaction; as well as, on virtual follower engagement and stickiness.

This study also categorized and examined the moderating effects exerted by the genres of informative influence of virtual influencer.

The purpose of this paper is to examine the influences of positive-framed and negative-framed green advertising on pro-environmental WTP. This study also explores the impacts of regulatory focus, environmental concern and pleasant level on green advertising effectiveness.

Data are collected from a within-participant between-group online experiment in China. The generalized estimating equation (GEE) is employed to investigate the impact of green advertising on WTP. Grouped regression and mediation analyses are conducted to explore the influences of regulatory focus, environmental concern and pleasure on advertising efficacy.

The experimental outcomes indicate that green advertising significantly increases participants’ pro-environmental WTP, and negative-framed advertising is more effective than its positive-framed counterpart. Prevention focus heightens receptivity to green advertising, and the relation of environmental concern to advertising effectiveness is inverted U-shaped. Pleasure mediates the effect of green advertising on the WTP, and this mediating role is influenced by emotional intensity when advertising is negatively framed.

Evidence suggests that green advertising may propel pro-environmental WTP by raising environmental awareness, but such a relationship remains severely understudied. As such, this study pioneers in exploring the impact of different-framed green advertising on pro-environmental WTP, extending the concept of green advertising to environmental management. By considering the influences of regulatory focus, environmental concern and pleasure, this study raises practical implications for designing green advertisements, such as increasing the usage of visual elements.

Accurate and automatic clothing pattern making is very important in personalized clothing customization and virtual fitting room applications. Clothing pattern generating as well as virtual clothing simulation is an attractive research issue both in clothing industry and computer graphics.

Physics-based method is an effective way to model dynamic process and generate realistic clothing animation. Due to conceptual simplicity and computational speed, mass-spring model is frequently used to simulate deformable and soft objects follow the natural physical rules. We present a physics-based clothing pattern generating framework by using scanned human body model. After giving a scanned human body model, first, we extract feature points, planes and curves on the 3D model by geometric analysis, and then, we construct a remeshed surface which has been formatted to connected quad meshes. Second, for each clothing piece in 3D, we construct a mass-spring model with same topological structures, and conduct a typical time integration algorithm to the mass-spring model. Finally, we get the convergent clothing pieces in 2D of all clothing parts, and we reconnected parts which are adjacent on 3D model to generate the basic clothing pattern.

The results show that the presented method is a feasible way for clothing pattern generating by use of scanned human body model.

The main contribution of this work is twofold: one is the geometric algorithm to scanned human body model, which is specially conducted for clothing pattern design to extract feature points, planes and curves. This is the crucial base for suit clothing pattern generating. Another is the physics-based pattern generating algorithm which flattens the 3D shape to 2D shape of cloth pattern pieces.

Multinational enterprises (MNEs) own and control technological resources and capabilities that make them critical actors in accelerating the transition toward net zero. Even beyond the energy sector, stakeholders are putting increasing pressure on MNEs to reduce the carbon intensity of their operations, that is, to improve their carbon performance. While there is unambiguous evidence that national climate policy is a critical catalyst for long-term carbon performance improvements, there is limited research on how MNEs’ carbon strategies react to climate policies. This chapter reviews the concepts, drivers, and strategies connected to carbon performance in the broader sustainability and management literature to clarify potential complementarities to international business (IB). The authors then highlight how MNEs will face increasing institutional complexity along two dimensions: (1) the structural diversity of institutional environments and (2) institutional dynamism, primarily reflected by public policy. The proposed conceptual framework maps these two dimensions to national and subnational levels, and the authors present two data sources that allow the quantitative analysis of country differences in the diversity and dynamism of national climate policy. The authors conclude that there are ample opportunities for IB researchers to explore MNEs’ strategic reactions to climate policy and to inform policymakers about the consequences of national climate policy in the global economy.

With the rise in wine consumption, accurate wine price forecasts have significantly impacted restaurant and hotel purchasing decisions and inventory management. This study aims to develop a precise and effective wine price point and interval forecasting model.

The proposed forecast model uses an improved hybrid kernel extreme learning machine with an attention mechanism and a multi-objective swarm intelligent optimization algorithm to produce more accurate price estimates. To the best of the authors’ knowledge, this is the first attempt at applying artificial intelligence techniques to improve wine price prediction. Additionally, an effective method for predicting price intervals was constructed by leveraging the characteristics of the error distribution. This approach facilitates quantifying the uncertainty of wine price fluctuations, thus rendering decision-making by relevant practitioners more reliable and controllable.

The empirical findings indicated that the proposed forecast model provides accurate wine price predictions and reliable uncertainty analysis results. Compared with the benchmark models, the proposed model exhibited superiority in both one-step- and multi-step-ahead forecasts. Meanwhile, the model provides new evidence from artificial intelligence to explain wine prices and understand their driving factors.

This study is a pioneering attempt to evaluate the applicability and effectiveness of advanced artificial intelligence techniques in wine price forecasts. The proposed forecast model not only provides useful options for wine price forecasting but also introduces an innovative addition to existing forecasting research methods and literature.

The rock drill’s drill tail experiences high-frequency fretting simultaneously in the rotational and axial directions. Due to the complex working characteristics and the low viscosity of the water medium, the pure water seal is susceptible to damage and failure. The purpose of this paper is to enhance the water seal’s performance.

The Y-shaped seal ring is modeled and simulated using orthogonal testing. Through analysis of the impact of various seal section parameters on sealing performance, the maximum contact stress and maximum Von Mises stress are selected as indicators of sealing effectiveness.

The maximum contact stress is proportional to lip thickness and chamfer length but inversely proportional to lip length. Meanwhile, the maximum Von Mises stress is directly influenced by lip depth and the included angle of the lip and drill tail but is inversely proportional to the lip thickness. The enhanced Y-shaped water seal sees reductions of 15% and 45% in maximum contact stress and maximum Von Mises stress, respectively.

This paper used analytical method and model that is helpful for design of the water seal’s structure in complex working characteristics and the low viscosity of the water medium.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2023-0366/

This paper aims to comprehensively review the preparation methods of superhydrophobic surfaces (SHPS) for corrosion protection of Mg alloy in recent years.

The preparation methods, wettability and corrosion resistance of SHPS on Mg alloy in the past three years are systematically described in this paper.

Two types of SHPS, including single-layer and multilayer coatings for corrosion protection of Mg alloy are summarized. Preparing multilayered coatings with multifunction is the current trend in developing SHPS on Mg alloy.

This paper reviewed the preparation methods and corrosion resistance of SHPS on Mg alloys. It provides a valuable reference for researchers to develop highly durable SHPS with excellent corrosion resistance for Mg alloys.