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With the rapid development of technology, 360° panorama on mobile as a very convenient way to present virtual reality has brought a new shopping experience to consumers. Usually, consumers get product information through virtual annotations in 360° panorama and then make a series of shopping behaviors. The visual design of virtual annotation significantly influences users' online visual search for product information. This study aims to investigate the influence of the visual design of virtual annotation on consumers' shopping experience in the online shopping interface of 360° panorama.

A 2 × 3 between-subject design was planned to help explore whether different display model of annotation (i.e. negative polarity and positive polarity) and different background transparency of annotation (i.e. 0% transparency, 25% transparency and 50% transparency) may affect users' task performance and their subjective evaluations.

(1) Virtual annotations with different background transparency affect user performance, and transparency has better visual search performance. (2) Virtual annotation background display mode may affect the user operation performance; the positive polarity of the virtual annotation is more convenient for the users' visual searching for product information. (3) When the annotation background transparency is opaque or semi-transparent, the negative polarity display is more favorable to the users' visual search. However, this situation is reversed when the annotation background transparency is 25%. (4) Participants preferred the presentation of positive polarity virtual annotations. (5) Regarding the degree of willingness to use and ease of understanding, participants preferred the negative polarity display for 0% background transparency or 50% background transparency. However, the opposite result was obtained for 25% background transparency.

The findings generated from the research can be a good reference for the development of virtual annotation visual design for mobile shopping applications.

1. Virtual annotation background transparency and background display mode are two essential attributes of 360° panoramas.

2. This study examined how virtual annotation background transparency and background display mode influence user performance and experience.

3. It is recommended to use a translucent or opaque annotation background with a negative polarity display.

4. Virtual annotation presentation with 25% background transparency facilitates consumer searching and comparison of product information.

5. Users prefer a positive polarity annotation display.

Virtual annotation background transparency and background display mode are two essential attributes of 360° panoramas.

This study examined how virtual annotation background transparency and background display mode influence user performance and experience.

It is recommended to use a translucent or opaque annotation background with a negative polarity display.

Virtual annotation presentation with 25% background transparency facilitates consumer searching and comparison of product information.

Users prefer a positive polarity annotation display.

This paper aims to propose a method of the safety boundary protection for unmanned aerial vehicles (UAVs) in the icing conditions.

Forty icing conditions were sampled in the continuous maximum icing conditions in the Appendix C of the Federal Aviation Regulation Part 25. Icing numerical simulations were carried out for the 40 samples and the anti-icing thermal load distribution in full evaporation mode were obtained. Based on the obtained anti-icing thermal load distribution, the surrogated model of the anti-icing thermal load distribution was established with proper orthogonal decomposition and Kriging interpolation. The weather research and forecasting (WRF) model was used for meteorological simulations to obtain the icing meteorological conditions in the target area. With the obtained icing conditions and surrogated model, the anti-icing thermal load distribution in the target area and the variation with time can be determined. According to the energy supply of the UAVs, the graded safety boundaries can be obtained.

The surrogated model can predict the effects of five factors, such as temperature, velocity, pressure, median volume diameter (MVD) and liquid water content (LWC), on the anti-icing thermal load quickly and accurately. The simulated results of the WRF mode agree well with the observed results. The method can obtain the graded safety boundaries.

The method has a reference significant for the safety of the UAVs with the limited energy supply in the icing conditions.

This study aims to examine connections between five variables, including innovation in environment-related technology (EI), trade openness (TRADE), CO₂ emissions (CO₂) and foreign direct investment (FDI) from 1994 to 2019.

This study used an extended joint connectedness technique and the time-varying parameter vector autoregression (TVP-VAR) method. The analysis focuses on the variables of innovation in environment-related technology (EI), trade openness (TRADE), CO₂ emissions (CO₂) and foreign direct investment (FDI) using data from 1994 to 2019.

The results demonstrate that innovation in environment-related technology and an openness to the global network captured by FDI are identified as crucial net transmitters of shocks. In addition, an openness to the global trade network captured by TRADE turns from a transmitter to a receiver of shocks and vice versa. Moreover, it can be seen that the impact of EI was significant in the first five years of the observed period, and it transmitted the largest shock in 1997.

With regard to policy implications, the findings offer valuable insights for investors and policymakers. As the tradeoff between business efficiency and environmental sustainability diminishes, it is essential for Vietnam’s economy and enterprises to embrace green and sustainable growth in line with global trends. In a world characterized by uncertainties and risks, enterprises need to develop strategies to manage risks and shocks arising from geopolitical tensions, input material supply, financial–monetary instability and natural disasters.

This study contributes to the existing literature in two significant ways. First, as previously emphasized, this paper represents the first attempt to investigate the relationship between economic globalization and environmental innovation. Second, this study proposes a novel methodology that is better suited for analyzing volatility interlinkages across different market types.

Every day, small and big incidents happen all over the world, and given the human, financial and spiritual damage they cause, proper planning should be sought to deal with them so they can be appropriately managed in times of crisis. This study aims to examine humanitarian supply chain models.

A new model is developed to pursue the necessary relations in an optimal way that will minimize human, financial and moral losses. In this developed model, in order to optimize the problem and minimize the amount of human and financial losses, the following subjects have been applied: magnitude of the areas in which an accident may occur as obtained by multiple attribute decision-making methods, the distances between relief centers, the number of available rescuers, the number of rescuers required and the risk level of each patient which is determined using previous data and machine learning (ML) algorithms.

For this purpose, a case study in the east of Tehran has been conducted. According to the results obtained from the algorithms, problem modeling and case study, the accuracy of the proposed model is evaluated very well.

Obtaining each injured person's priority using ML techniques and each area's importance or risk level, besides developing a bi-objective mathematical model and using multiple attribute decision-making methods, make this study unique among very few studies that concern ML in the humanitarian supply chain. Moreover, the findings validate the results and the model's functionality very well.

The purpose of this study is to investigate the application of non-destructive testing methods in measuring bearing oil film thickness to ensure that bearings are in a normal lubrication state. The oil film thickness is a crucial parameter reflecting the lubrication status of bearings, directly influencing the operational state of bearing transmission systems. However, it is challenging to accurately measure the oil film thickness under traditional disassembly conditions due to factors such as bearing structure and working conditions. Therefore, there is an urgent need for a nondestructive testing method to measure the oil film thickness and its status.

This paper introduces methods for optically, electrically and acoustically measuring the oil film thickness and status of bearings. It discusses the adaptability and measurement accuracy of different bearing oil film measurement methods and the impact of varying measurement conditions on accuracy. In addition, it compares the application scenarios of other techniques and the influence of the environment on detection results.

Ultrasonic measurement stands out due to its widespread adaptability, making it suitable for oil film thickness detection in various states and monitoring continuous changes in oil film thickness. Different methods can be selected depending on the measurement environment to compensate for measurement accuracy and enhance detection effectiveness.

This paper reviews the basic principles and latest applications of optical, electrical and acoustic measurement of oil film thickness and status. It analyzes applicable measurement methods for oil film under different conditions. It discusses the future trends of detection methods, providing possible solutions for bearing oil film thickness detection in complex engineering environments.