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This study analyzes the blade channel vortices inside Francis runner with a particular focus on the identification of different types of vortices and their causes.

A single-flow passage of the Francis runner with refined mesh and periodic boundary conditions was used for the numerical simulation to reduce the computational resource. The steady-state Reynolds-averaged Navier–Stokes equations closed with the k-ω shear–stress transport (SST) turbulence model were solved by ANSYS CFX to determine the flow field. The vortices were identified by the second largest eigenvalue of velocity.

Four types of vortices were identified inside the runner. Three types were related to the inlet flow. The last one (Type 4) was caused by the reversed flow near the runner crown and had the lowest pressure inside the core near the runner outlet. Thus, in the blade channel vortex inception line, Type 4 vortex would appear earlier than the other three ones. Besides, the Type 4 vortex emerged from the crown and shed toward the blade-trailing edge. And its location moved from near the crown down to near the band when the unit speed increased or unit discharge decreased.

Although the refined mesh was used and the main vortices in the Francis runner were well predicted, the current mesh is not enough to accurately predict the lowest pressure in the channel vortex core.

This knowledge is instructive in the runner blade design and troubleshooting related to the channel vortex.

This study gives an overview of the main observed blade channel vortices and their causes, and points out the important role the reversed flow plays in the formation of blade channel vortices. This knowledge is instructive in the runner blade design and troubleshooting related to blade channel vortices.

The purpose of this paper is to present a path planning algorithm for a non‐circular shaped mobile robot to autonomously navigate in an unknown area for humanitarian demining. For that purpose the path planning problem comes down to planning a path from some starting location to a final location in an area so that the robot covers all the reachable positions in the area while following the planned path.

The proposed algorithm uses occupancy grid map representation of the area. Every free cell in the grid map represents a node in the graph being searched to find the complete coverage path. The complete coverage path is followed by the dynamic window algorithm, which includes robot's kinematic and dynamic constraints.

The proposed algorithm finds the complete coverage path in the graph accounting for the dimensions of the mobile robot, where non‐circular shaped robots can be easily included. The algorithms are implemented under the ROS (robot operating system) and tested in the stage 3D simulator for mobile robots with a randomly generated simulation map of an unknown area.

Some parts of the area close to obstacles are hard to cover due to complex non‐circular shaped robot and non‐perfect path following. The future work should include better path following algorithm.

The proposed algorithm has shown itself as effective and could meet the working demands of humanitarian demining.

The algorithm proposed in the paper enables complete coverage path planning of non‐circular shaped robots in unknown areas.

The goal of this work is to evaluate how digital transformation disclosure in corporate news and press releases affects stock prices. We examine American and Chinese companies from the energy and industry sectors for two periods: pre-COVID-19 and during the COVID-19 pandemic.

To estimate the effects of disclosure of information related to digital transformation, we applied the bag-of-words (BOW) method. As the benchmark dictionary, we used Kindermann et al. (2021), with the addition of original dictionaries created via Latent Dirichlet allocation (LDA) analysis. We also employed panel regression analysis and random forest.

For USA energy sector, all aspects of digital transformation were insignificant in pre-COVID-19 period, while sustainability topics became significant during the pandemic. As for the Chinese energy sector, digital strategy implementation was significant in pre-pandemic period, while digital technologies adoption and business model innovation became relevant in COVID-19 period. The results show the greater significance of digital transformation aspects for industrials sectors compared to the energy sector. The result of random forest analysis proves the efficiency of the authors’ dictionary which could be applied in practice. The developed methodology can be considered relevant.

The research contributes to the existing literature in theoretical, empirical and methodological ways. It applies signaling and information asymmetry theories to the financial markets, digital transformation being used as an instrument. The methodological contribution of this article can be described in several ways. Firstly, our data collection process differs from that in previous papers, as the data are gathered “from investor’s point of view”, i.e. we use all public information published by the company. Secondly, in addition to the use of existing dictionaries based on Kindermann et al. (2021), with our own modifications, we apply the original methodology based on LDA analysis. The empirical contribution of this research is the following. Unlike past works, we do not focus on particular technologies (Hong et al., 2023) connected with digital transformation, but try to cover all multi-dimensional aspects of the transformational process and aim to discover the most significant one.

In recent years, the application of artificial intelligence and digital technology has increasingly become a priority for online retailers. It is crucial to choose a way to make use of human–computer interaction (HCI) design to exert the positive influence of intelligent technology on consumer welfare. Despite the increasing use of HCI design in online retail context, there remain limitations in their effect of consumer well-being improvement. Although there is extensive literature in the field of consumer well-being improvement, few studies have empirically examined how HCI design drives the improvement of consumer well-being in the online retail context. Therefor, this study aims to deeply and systematically analyze the psychological mechanism between HCI and consumer well-being in the online retail environment.

The empirical analysis is based on data collection of 476 samples of online shoppers through the online survey method. From the perspective of autonomy, this study deeply analyzes the influence mechanism of different dimensions of HCI perception on consumer well-being.

The results indicated that autonomy plays a positive intermediary role in the impact of perceived connectivity, perceived personalization, perceived control and perceived responsiveness on the eudaimonia and hedonic enjoyment. Also, it revealed that psychological resistance negatively regulates the impact of perceived connectivity, perceived personalization and perceived control on autonomy, while experience purchase positively regulates the impact of autonomy on hedonic enjoyment.

This paper expands the research situation of consumer well-being by making integration of the dual structure of subjective well-being and psychological well-being to define the psychological mechanism and boundary conditions of the impact of HCI perception on consumer well-being. The main contribution of this study is to provide enlightenment for online retail enterprises to improve HCI design and help consumers enhance long-term well-being.

This paper aims to present a distributed Bayesian approach with connectivity maintenance to manage a multi-agent network search for a target on a two-dimensional plane.

The Bayesian framework is used to compute the local probability density functions (PDFs) of the target and obtain the global PDF with the consensus algorithm. An inverse power iteration algorithm is introduced to estimate the algebraic connectivity λ₂ of the network. Based on the estimated λ₂, the authors design a potential field for the connectivity maintenance. Then, based on the detection probability function, the authors design a potential field for the search target. The authors combine the two potential fields and design a distributed gradient-based control for the agents.

The inverse power iteration algorithm can distributed estimate the algebraic connectivity by the agents. The agents can efficient search the target with connectivity maintenance with the designed distributed gradient-based search algorithm.

Previous study has paid little attention to the multi-agent search problem with connectivity maintenance. Our algorithm guarantees that the strongly connected graph of the multi-agent communication topology is always established while performing the distributed target search problem.

Innovation means innovation. It enables companies to grow and compete with other companies. However, innovation studies also increase the welfare level of the countries. One of the most important topics in innovation studies is research and development (R&D). R&D enables companies to identify their current problems and lay the groundwork for new products and services. In this way, it contributes to the profit of the companies. The purpose of this study is to determine the effect of innovation on the share value of the company. In the study, the data are collected from Turkey during the period 1991–2019. However, the study was tested by Engle–Granger Cointegration analysis. As a result, it has been determined that there is a long-term relationship between R&D expenditures and the company’s share value. In this context, companies need to focus on R&D expenditures to increase their share values. For this issue, they need to increase their liquidity. In addition, the R&D departments in the company need to be increased. Companies need to prepare a separate budget for R&D studies.

This systematic review, following preferred reporting items for systematic reviews and meta-analysis guidelines, rigorously investigates the emergent role of virtual reality (VR) technology in human movement training. The purpose of this study is to explore the effectiveness and evolution of VR in enhancing movement training experiences.

Acknowledging its pivotal role in diverse applications, such as sports and rehabilitation, human movement training is currently experiencing accelerated evolution, facilitated by the proliferation of wearable devices and mobile applications. This review conducted an exhaustive search across five different electronic databases, such as Web of Science, PubMed and ProQuest, resulting in the selection of 69 eligible articles published within the past five years. It also integrates 40 studies into a narrative summary, categorized based on the level of immersion offered by respective VR systems.

Enhanced immersion in VR potentially augments the effectiveness of movement training by engendering more realistic and captivating experiences for users. The immersive and interactive environments provided by VR technology enable tailored training experiences accompanied by precise, objective feedback. This review highlights the benefits of VR in human movement training and its potential to revolutionize the way training is conducted.

This systematic review contributes significantly to the existing literature by providing a comprehensive examination of the efficacy and evolution of VR in human movement training. By organizing the findings based on the level of immersion offered by VR systems, it provides valuable insights into the importance of immersion in enhancing training outcomes. In addition, this study identifies the need for future research focusing on the impacts of VR on learning and performance, as well as strategies to optimize its effectiveness and improve accessibility.