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Fully-actuated unmanned aerial vehicles (UAVs) are a growing and promising field of research, which shows advantages for aerial physical interaction. The purpose of this paper is to construct a force sensor-denied control method for a fully-actuated hexarotor to conduct aerial interaction with accurate force exerted outward.

First, by extending single-dimension impedance model to the fully-actuated UAV model, an impedance controller is designed for compliant UAV pose/force control. Then, to estimate the interaction force between UAV end-effector and external environment accurately, combined with super-twisting theory, a nonlinear force observer is constructed. Finally, based on impedance controller and estimated force from observer, an interaction force regulation method is proposed.

The presented nonlinear observer-based impedance control approach is validated in both simulation and environments, in which the authors try to use a fully-actuated hexarotor to accomplish the task of aerial physical interaction finding that a specified force is able to be exerted to environment without any information from force sensors.

A solution of aerial physical interaction for UAV system enabling accurate force exerted outward without any force sensors is proposed in this paper.

This paper aims to tackle the problem for a fully actuated unmanned aerial vehicle (FUAV) to perform physical interaction tasks in the Global Positioning System-denied environments without expensive motion capture system (like VICON) under disturbances.

A tether-based positioning system consisting of a universal joint, a tether-actuated absolute position encoder and an attitude sensor is designed to provide reliable position feedback for the FUAV. To handle the disturbances, including the tension force caused by the taut tether, model uncertainties and other external disturbances such as aerodynamic disturbance, a hybrid disturbance observer (HDO) combining the position-based method and momentum-based technology with force sensor feedback is designed for the system. In addition, an HDO-based impedance controller is built to allow the FUAV interacting with the environment and meanwhile rejecting the disturbances.

Experimental validations of the proposed control algorithm are implemented on a real FUAV with the result of nice disturbance rejection capability and physical interaction performance.

A cheap alternative to indoor positioning system is proposed, with which the FUAV is able to interact with external environment and meanwhile reject the disturbances under the help of proposed hybrid disturbance observer and the impedance controller.

Previous studies showed that the unconscious-intuitive strategy resulted in a better choice for it is more predictive of actual interest. This benefit may be influenced by occupational engagement, for the dual process of career decisions takes it as a tool for multidevelopment and optimal adjustment. Thus, we replicated (and extended) the study of Motl et al. (2018) through two experiments to identify the role of three pre-decisional strategies and then explore the combined effects of occupational engagement and these strategies. The purpose of this paper is to address these issues.

The authors replicated (and extended) the study of Motl et al. (2018) through two experiments. First, both studies adopted generalized linear mixed-effects models for statistical analyses to distinguish random and fixed effects. Second, Study 2 used a computer-based process-tracing program called “Mouselab” to explore the effect of the pre-decisional strategy self-generated on participants' interest appraisals over time.

Study 1 found that engagement helped promote participants' interest experience when decisions as usual and the intuitive strategy did not produce optimal choices. Further, people with more prior knowledge about situations no longer achieved as many benefits from their allocated strategy (i.e. rational strategy) as those with less. Study 2 failed to find adequate advantages of the intuitive strategy. Specifically, people with less search depth (the heuristic-intuitive strategy) were more interested in their choices. Nevertheless, when the strategy was manipulated as variability of search (VS), it only found the promotion of engagement, but it neither found the interaction between engagement and strategy nor did strategy itself.

The present paper provides mixed support for adaptive career decision-making. Career counselors can use occupational engagement levels as a reference for pre-decisional strategy selection and coach clients to adopt a proper decision-making process/method to make interest forecasts.

The paper aims to investigate the impact of economic policy uncertainty (EPU) (i.e. uncertainty due to government policies) on fine wine prices.

The paper uses the Baker et al. (2016) monthly news-based measure of EPU for the leading wine markets: the USA, the UK, France, Germany and China in conjunction with monthly fine wine pricing data from the London International Vintners Exchange (Liv-ex). The wine sub-indices used are the Liv-ex 500 (Bordeaux), Burgundy 150, Champagne 50, Rhone 100, Italy 100, California 50, Port 50 and Rest of the World 50. The Prais–Winsten and Cochrane–Orcutt regressions are used for our analyses to correct for effects of serial correlation. Time lags are chosen based on the appropriate information criterion.

Changes in EPU levels negatively impact changes in the Liv-ex 500 index for all our leading wine markets except France, the Champagne 50 index for the UK and the Burgundy 150 and the Rhone 100 indices for Germany, with the effects being significant for at least up to a quarter before EPU is detected. The authors did not find significant results for the EPU of France.

The paper aims to provide insights into whether EPU creates opportunities or threats for investors and wineries.

A forward-looking news-based EPU measure is used to gain insights into how the different Liv-ex sub-indices react to increases in uncertainty centered around government policies across a sample of different countries.

With the rapid change that has taken place with digitalization and data-driven approaches in supply chains, business environment become more competitive and reaching sustainability in supply chains become even more challenging. In order to manage supply chains properly, in terms of considering environmental, social and economic impacts, organizations need to deal with huge amount of data and improve organizations' data management skills. From this view, increased number of stakeholders and dynamic environment reveal the importance of data-driven technologies in sustainable supply chains. This complex structure results in new kind of risks caused by data-driven technologies. Therefore, the aim of the study to analyze potential risks related to data privacy, trust, data availability, information sharing and traceability, i.e. in sustainable supply chains.

A hybrid multi-criteria decision-making (MCDM) model, which is the integration of step-wise weight assessment ratio analysis (SWARA) and TOmada de Decisao Interativa Multicriterio (TODIM) methods, is going to be used to prioritize potential risks and reveal the most critical sustainability dimension that is affected from these risks.

Results showed that economic dimension of the sustainable supply chain management (SSCM) is the most critical concept while evaluating risks caused by data-driven technologies. On the other hand, risk of data security, risk of data privacy and weakness of information technology systems and infrastructure are revealed as the most important risks that organizations should consider.

The contribution of the study is expected to guide policymakers and practitioners in terms of defining potential risks causes by data-driven technologies in sustainable supply chains. In future studies, solutions can be suggested based on these risks for achieving sustainability in all stages of the supply chain causes by data-driven technologies.

Humanity and all life depend on the natural environment of Planet Earth, and that environment is in acute crisis across land, sea and air. One of a set of commentaries on how service can address the UN’s sustainable development goals (SDGs), the authors focus on environmental goals SDG 13 (climate action), SDG 14 (life below water) and SDG 15 (life on land). This paper aims to propose a conceptual framework that incorporates the natural environment into transformative services.

The authors trace the evolution of service thinking about the natural environment, from a stewardship perspective of the environment as a set of resources to be managed, through an acknowledgement of nonhuman organisms as actors that can participate in service exchange, towards an emergent concept of ecosystems as integrating human social actors and other biological actors who engage fully in value co-creation.

The authors derive a framework integrating human and other life forms as co-creating actors, drawing on shared natural resources to achieve mutualism, where each actor can have a net benefit from the relationship. Future research questions are posited that may help services research address SDGs 13–15.

The framework integrates ideas from environmental ecosystem literature to inform the nature of ecosystems. By integrating environmental actors and ecological insights into the understanding of service ecosystems, service scholars are well placed to make unique contributions to the global challenge of creating a sustainable future.

Groups typically are composed of members with different knowledge, information, and expertise. Group discussion provides the means by which members can communicate their unique knowledge to reach better group decisions, develop a shared system for remembering and retrieving knowledge, and establish their expertise through enacted performance. In this chapter, three streams of research are reviewed that explore knowledge communication in groups: Hidden profiles, transactive memory systems, and a performative view of expertise. Each of these three research streams complements and informs the other. Across these three research streams, 10 major research findings are identified. We offer three research directions that include integrating these research streams, examining knowledge communication in the context of emerging technology (e.g., artificial intelligence), and studying effects of knowledge diversity in conjunction with surface-level diversity (e.g., member race).

The literature that is presently available on sustainable supply chain management (SSCM) combining optimization and industry 4.0 techniques falls short in its depictions of the recent developments, budding pertinent areas and the importance of SSCM in the growth of industrial economies around the world. This article's main objective is to analyze current trends, highlight the latest initiatives and perform a meta-analysis of the literature that is currently accessible in the SSCM area with a special focus on optimization and industry 4.0 techniques. The paper also proposes a conceptual framework that will assist in illuminating how the ideas of optimization and industry 4.0 may contribute to realizing sustainability in supply chains.

The proposed study systematically reviews 85 research publications published between 2010 and 2022 in referenced peer-reviewed journals in diverse fields, including engineering, business and management, services and healthcare. Numerous categories are considered throughout the examination of the literature, including year-wise publications, prominent journals, type of research design, concerned industry and research technique used.

The study demonstrates a deeper comprehension of the literature in the field and its evolution throughout numerous industry sectors, which is helpful for both practitioners and academics. The results from the content analysis highlight various future research opportunities in the domain.

This is one of the first research articles that have attempted to establish, analyze and highlight the current trends and initiatives in the SSCM domain from an optimization and industry 4.0 techniques viewpoint. The cluster-based future research propositions also enhance the novelty of the study.

During running-in, the change in the honed cylinder liner surface alters the performance and efficiency of the piston ring-pack system. The present paper, thus, aims to investigate the surface topography and wear and friction evolution of a cylinder liner surface during the running-in tests on a reciprocating ring–liner tribometer under a mixed lubrication regime. After an initial period of rapid wear termed “running-in wear”, a relatively long-term steady-state surface topography can emerge. A numerical model is developed to predict the frictional performance of a piston ring-pack system at the initial and steady-state stages.

The liner surfaces are produced by slide honing (SH) and plateau honing (PH). The bearing area parameter (Rk family), commonly used in the automotive industry, is used to quantitatively characterize the surface topography change during the running-in process. A wear volume-sensitive surface roughness parameter, Rktot, is used to show the wear evolution.

The experimental results show that a slide-honed surface leads to reduced wear, and it reduces the costly running-in period compared to the plateau-honed surface. The simulation results show that running-in is a beneficial wear process that leads to a reduced friction mean effective pressure at the steady-state.

To simulate the mixed lubrication performance of a ring–liner system with non-Gaussian roughness, a one-dimensional homogenized mixed lubrication model was established. The real surface topography instead of its statistical properties is taken into account.

The purpose of this paper is to study the real-time change of surface roughness at different small regions of piston rings during running-in process. Meanwhile, the effects of real-time change of the rough surface topography on the lubrication and friction of piston rings are investigated.

An uneven wear model has been developed to research the running-in behavior at the different small regions of piston rings. The model is verified by comparing the simulation results with the experimental results on a reciprocating friction and wear test rig.

This research shows that the wear process of piston ring surface is uneven during running-in. At most time of the operating cycle except the vicinity of top dead center and bottom dead center, the minimum oil film thickness ratio increases while the friction force and power loss decrease after the running-in period.

Through this research, the running-in behavior of piston rings is investigated in detail. The interaction between the running-in and the lubrication and friction of piston rings is understood more deeply.