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This paper aims to introduce a novel structure for the physical internet (PI)–enabled sustainable supplier selection and inventory management problem under uncertain environments.

To address hybrid uncertainty both in the objective function and constraints, a novel interactive hybrid multi-objective optimization solution approach combining Me-based fuzzy possibilistic programming and interval programming approaches is tailored.

Various numerical experiments are introduced to validate the feasibility of the established model and the proposed solution method.

Due to its interconnectedness, the PI has the opportunity to support firms in addressing sustainability challenges and reducing initial impact. The sustainable supplier selection and inventory management have become critical operational challenges in PI-enabled supply chain problems. This is the first attempt on this issue, which uses the presented novel interactive possibilistic programming method.

People continue to become more liberated and individualised day by day. They look for ways to somehow get out of any situation that restricts them, tend to get rid of their typical holiday patterns and travel alone, without being stuck within anyone else's borders, precisely as they want. In addition, people can travel alone to discover themselves, meet different cultures, relieve stress and learn new skills. Women travel alone more than men, although they face more difficulties than men. The experiences of women solo travellers suggest that this form of travel can provide a meaningful foundation for advancing gender equality. By challenging gender roles and expectations, empowering women to assert their autonomy and agency and creating opportunities for community-building and solidarity, solo travel can help to transform social norms and promote gender equity.

This chapter aims to build a body of knowledge that will have a widespread impact based on available data on the relationship of women solo travellers to gender equality. It also examines the effects of women solo travellers on gender equality based on secondary data sources. This chapter, designed as conceptual research with descriptive analysis and document analysis, is important in revealing what the indirect gains of women solo travellers can be for gender equality, the fifth of the United Nations Development Programme (UNDP) Sustainable Development Goals.

Choosing the proper selling format for online retail has long been a critical issue for many platforms to consider, whereas the emergence and popularity of live-streaming have had a massive impact on the platform's business. As a result, selecting the suitable operating strategy for the live channel has become another critical issue for platforms. In such a context, what will be the impact of live-streaming on selling formats?

In order to explore these issues, we identified two selling formats (wholesale reselling or agency selling) as well as two operating strategies (introduce or discard). Thereby, four channel-structures are constructed, namely the reselling-discard model (WN), the reselling-introduce model (WL), the agency-discard model (AN), and the agency-introduce model (AL). We comprehensively compare how different structures affect stakeholders' interests, consumer surplus, and social welfare through equilibrium analyses.

These results help clarify the impact of critical factors (e.g. self-effort attribute, cross-effort attribute, and commission ratio) on the choice of models. We find that regardless of the selling agreement between the manufacturer and the platform, the introduction of a live store is necessary; specifically, when the commission ratio is high, the platform's optimal decision is first to sign an agency agreement and then apply live selling (AL); conversely, when the commission ratio is low, the platform's optimal strategy is first to enable the live channel and then to select the reselling format (WL), together, this also reveals, from a theoretical perspective.

Our study includes the dual analysis of selling formats and channel operations, considering the inherent dual attributes of service efforts and the external competitive environment.

When emergencies occur, the attention of the public towards emergency information on social media in a specific time period forms the emergency information popularity evolution patterns. The purpose of this study is to discover the popularity evolution patterns of social media emergency information and make early predictions.

We collected the data related to the COVID-19 epidemic on the Sina Weibo platform and applied the K-Shape clustering algorithm to identify five distinct patterns of emergency information popularity evolution patterns. These patterns include strong twin peaks, weak twin peaks, short-lived single peak, slow-to-warm-up single peak and slow-to-decay single peak. Oriented toward early monitoring and warning, we developed a comprehensive characteristic system that incorporates publisher features, information features and early features. In the early features, data measurements are taken within a 1-h time window after the release of emergency information. Considering real-time response and analysis speed, we employed classical machine learning methods to predict the relevant patterns. Multiple classification models were trained and evaluated for this purpose.

The combined prediction results of the best prediction model and random forest (RF) demonstrate impressive performance, with precision, recall and F1-score reaching 88%. Moreover, the F1 value for each pattern prediction surpasses 87%. The results of the feature importance analysis show that the early features contribute the most to the pattern prediction, followed by the information features and publisher features. Among them, the release time in the information features exhibits the most substantial contribution to the prediction outcome.

This study reveals the phenomena and special patterns of growth and decline, appearance and disappearance of social media emergency information popularity from the time dimension and identifies the patterns of social media emergency information popularity evolution. Meanwhile, early prediction of related patterns is made to explore the role factors behind them. These findings contribute to the formulation of social media emergency information release strategies, online public opinion guidance and risk monitoring.

Solo travelling has been one of the rising types of travelling, especially after the pandemic. This study is focused on solo female travellers and aims to present a comprehensive literature review on solo travelling. For this aim, a detailed literature review is performed. The significance of this study lies in the recent developments in countries like Iran regarding women's rights, and it needs to be understood that women are powerful, and they can prove that by travelling solo. This study is aimed to contribute to women's empowerment because it is important to set various examples and pave the way for the next generations towards a more free, enlightened, conscious and modern future. As a segment, solo female travellers need to be characterised in terms of their demographics and motivations for solo travelling, and destinations should take precautions for their safety and security to be represented and promoted as a safe and modern location where the freedom of each individual is secured.

Surface acoustic wave (SAW) sensors have attracted great attention worldwide for a variety of applications in measuring physical, chemical and biological parameters. However, stability has been one of the key issues which have limited their effective commercial applications. To fully understand this challenge of operation stability, this paper aims to systematically review mechanisms, stability issues and future challenges of SAW sensors for various applications.

This review paper starts with different types of SAWs, advantages and disadvantages of different types of SAW sensors and then the stability issues of SAW sensors. Subsequently, recent efforts made by researchers for improving working stability of SAW sensors are reviewed. Finally, it discusses the existing challenges and future prospects of SAW sensors in the rapidly growing Internet of Things-enabled application market.

A large number of scientific articles related to SAW technologies were found, and a number of opportunities for future researchers were identified. Over the past 20 years, SAW-related research has gained a growing interest of researchers. SAW sensors have attracted more and more researchers worldwide over the years, but the research topics of SAW sensor stability only own an extremely poor percentage in the total researc topics of SAWs or SAW sensors.

Although SAW sensors have been attracting researchers worldwide for decades, researchers mainly focused on the new materials and design strategies for SAW sensors to achieve good sensitivity and selectivity, and little work can be found on the stability issues of SAW sensors, which are so important for SAW sensor industries and one of the key factors to be mature products. Therefore, this paper systematically reviewed the SAW sensors from their fundamental mechanisms to stability issues and indicated their future challenges for various applications.

Modular capacity units enable rapid reconfiguration, providing tactical flexibility to efficiently meet customer demand during disruptions and ensuring sustainability. Moreover, the Physical Internet (PI) enhances the potential of modular capacity in addressing efficiency, sustainability, and resilience challenges. To evaluate the sustainability and resilience advantages of the PI-enabled reconfigurable modular system (PI-M system), this paper studies a PI-enabled sustainable and resilient production-routing problem with modular capacity.

We develop a multi-objective optimization model to assess the sustainability and resilience benefits of combining PI and modular capacity in a chemical industry case study. A hybrid solution approach, combining the augmented e-constraint method, construction heuristic, and hybrid adaptive large neighborhood search, is developed.

The experimental results reveal that the proposed solution approach is capable of obtaining better solutions than the Gurobi and the existing heuristic in a shorter running time. Moreover, compared with the traditional system, the PI only and traditional with modular capacity systems, PI-M system has significant advantages in both sustainability and resilience.

To the best of our knowledge, this study is the first to integrate the PI and modular capacity and investigate sustainability and resilience in the production-routing problem.

The purpose of this study is to propose a fractal model of thermal contact conductance of rough surfaces based on axisymmetric cosinusoidal asperity.

The effects of contact load, fractal dimension, fractal roughness and friction coefficient on the thermal contact conductance of rough surfaces were investigated in this study.

The findings suggest that as the contact load increases, the thermal contact conductance of rough surfaces also increases. In addition, an increase in the fractal dimension corresponds to an increase in the thermal contact conductance. Conversely, an increase in fractal roughness leads to a decrease in thermal contact conductance. The smaller the friction coefficient, the lower the thermal contact conductance of the rough surface. In practical engineering applications, it is possible to achieve the desired thermal contact conductance of rough surfaces by selecting surfaces with appropriate roughness.

A fractal model of thermal contact conductance of rough surfaces based on axisymmetric cosinusoidal asperity was established in this study. The findings of this study offer a theoretical foundation for investigating the thermal contact conductance of rough surfaces.

Over the past two decades, the study of team resilience has evolved from focusing primarily on team performance to recognizing its importance in various aspects of team functioning, including psychological health, teamwork, and overall Well-Being. This evolution underscores the need for a broader, more inclusive understanding of team resilience, advocating for a shift from a narrow performance-centric view to a holistic perspective that encompasses the multifaceted impact of resilience on teams.

In advocating for this holistic perspective, this chapter reviews the extant literature, highlighting that resilience is not merely about sustaining performance but also about fostering a supportive, adaptive, and psychologically safe environment for team members. Significant areas for further exploration, including the nuanced nature of adversities teams face, the processes underpinning resilient behaviors, and the broad spectrum of outcomes resilience can influence beyond task performance are also discussed.

The chapter serves as a call to action for a more inclusive examination of how resilience manifests and benefits teams in organizational settings. The proposed shift in perspective aims to deepen understanding of team resilience, promoting strategies for building resilient teams that thrive not only in performance but in all aspects of their functioning.

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.