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The purpose of this study is to introduce the top-level design ideas and the overall architecture of earthquake early-warning system for high speed railways in China, which is based on P-wave earthquake early-warning and multiple ways of rapid treatment.

The paper describes the key technologies that are involved in the development of the system, such as P-wave identification and earthquake early-warning, multi-source seismic information fusion and earthquake emergency treatment technologies. The paper also presents the test results of the system, which show that it has complete functions and its major performance indicators meet the design requirements.

The study demonstrates that the high speed railways earthquake early-warning system serves as an important technical tool for high speed railways to cope with the threat of earthquake to the operation safety. The key technical indicators of the system have excellent performance: The first report time of the P-wave is less than three seconds. From the first arrival of P-wave to the beginning of train braking, the total delay of onboard emergency treatment is 3.63 seconds under 95% probability. The average total delay for power failures triggered by substations is 3.3 seconds.

The paper provides a valuable reference for the research and development of earthquake early-warning system for high speed railways in other countries and regions. It also contributes to the earthquake prevention and disaster reduction efforts.

This paper delves into evaluating the effectiveness of warning messages as a deterrent against excessive fat consumption. It examines how consumers perceive the fat content of food products when presented with two distinct label types: (1) a textual warning, providing succinct information about the fat content, and (2) a pictorial warning, offering a visual representation that immediately signifies the fat content.

Two quantitative studies were carried out. Study 1 employed a questionnaire to evaluate the efficacy of textual and pictorial warning messages on high- and low-fat food products. Similarly, Study 2 replicated this comparison while incorporating a neuromarketing instrument to gauge participants’ cerebral reactions.

Results indicate that pictorial warnings on high-fat foods significantly deter consumers’ purchasing intentions. Notably, these pictorial warnings stimulate the left prefrontal area of the cerebral cortex, inducing negative emotions in consumers and driving them away from high-fat food items.

While the influence of images over text in shaping consumer decisions is well understood in marketing, this study accentuates the underlying mechanism of such an impact through the elicitation of negative emotions. By understanding this emotional pathway, the paper presents fresh academic and managerial perspectives, underscoring the potency of pictorial warnings in guiding consumers towards healthier food choices.

1. Textual warnings do not seem to discourage high-fat product consumption.

2. A pictorial warning represents the fat content of an equivalent product.

3. Pictorial warnings decrease the intention to purchase a high-fat product.

4. Pictorial warnings determine an increase in negative emotions.

Textual warnings do not seem to discourage high-fat product consumption.

A pictorial warning represents the fat content of an equivalent product.

Pictorial warnings decrease the intention to purchase a high-fat product.

Pictorial warnings determine an increase in negative emotions.

Hazard warning schemes provide efficient hazard recognition and promote project safety. Nevertheless, these schemes perform poorly because the warning information is calibrated for individual characters and is not prioritized for the entire system. This study proposes a hazard warning scheme that prioritizes hazard characters from the inspection process based on the inspectors' experience.

First, hazard descriptions were decomposed into their characters, forming a double-layer network. Second, warning schemes based on cascading effects were proposed. Third, character-based warning schemes were simulated for various experiences.

The results show that when a specific hazard is detected, the degree centrality is the most effective parameter for prioritization, and hazard characters should be prioritized based on betweenness centrality for experienced inspectors, whereas degree centrality is preferred for novice inspectors.

The warning scheme theoretically supplements the information-processing theory in construction hazard warnings and provides a practical warning scheme with priority for the development of automated hazard navigation systems.

Heavy fog results in low visibility, which increases the probability and severity of traffic crashes, and fog warning system is conducive to the reduction of crashes by conveying warning messages to drivers. This paper aims at exploring the effects of dynamic message sign (DMS) of fog warning system on driver performance.

First, a testing platform was established based on driving simulator and driver performance data under DMS were collected. The experiment route was consisted of three different zones (i.e. warning zone, transition zone and heavy fog zone), and mean speed, mean acceleration, mean jerk in the whole zone, ending speed in the warning zone and transition zone, maximum deceleration rate and mean speed reduction proportion in the transition zone and heavy fog zone were selected. Next, the one-way analysis of variance was applied to test the significant difference between the metrics. Besides, drivers’ subjective perception was also considered.

The results indicated that DMS is beneficial to reduce speed before drivers enter the heavy fog zone. Besides, when drivers enter a heavy fog zone, DMS can reduce the tension of drivers and make drivers operate more smoothly.

This paper provides a comprehensive approach for evaluating the effectiveness of the warning system in adverse conditions based on the driving simulation test platform. The method can be extended to the evaluation of vehicle-to-infrastructure technology in other special scenarios.

The purpose of this paper is to research the impact of foreign direct investment (FDI) on China's economic growth, so as to measure reasonable scales of FDI and the safe coefficient of China's FDI utilization, make timely predictions, and suggest specific foreign capital management and controlling strategies for the policy makers to adopt under various conditions.

This paper builds early warning systems (EWSs)for China's FDI utilization, applies grey correlation model GM (1,1) to predict early warning indexes, and uses both of the grey correlation and analytic hierarchy process (AHP) to evaluate the weights of the indexes.

The paper finds that FDI can promote China's economic growth, make great contribution to the technology spillover and improve China's employment environment as well as the quality of employment. But its contribution is less than the domestic capital in the aspects of China's industrial structure, area structure and trade structure adjustment, and more seriously, FDI exacerbates the imbalance of the area distribution in China. Moreover, foreign capital focuses on the occupation and monopoly of the domestic market, which will reduce import and export trade and harm the development of China's economy.

Owing to data constraints, this paper is not detailed and comprehensive enough, and needs further exploration in the empirical work.

Given the strong evidence of the EWS for FDI utilization, this paper finds a precise way to evaluate the influence of FDI on China's economic growth, by which the government can implement different capital management and controlling strategies to smooth the openness process of FDI in China.

This paper applies EWS into the FDI utilization to evaluate the safe coefficient and achieve the warning indexes, which are evaluated by the combination of the grey correlation and AHP.

The purpose of this paper is to present an overview of the concept of early warning signs in projects and explain how a performance measurement system can be utilized as a source of data for an early warning approach signaling that a project is about to experience problems at some stage in the future.

Combination of action research and semi‐structured interviews and document analysis supplemented by a post‐mortem analysis after project close‐out.

Detection of early warning signals in projects can be better enabled through the application of a performance measurement system with properly defined key performance indicators. Utilization of this tool can positively affect the overall success of the project.

The case study involved only one project from the oil and gas industry.

The empirical case study was developed to illustrate the usefulness of exploiting a performance measurement system in a project. A procedure was demonstrated for developing and implementing an early warning system based on performance measurement, and specific performance indicators have been described for other projects to copy.

This paper highlights the gap in the literature concerning the link between early warning and project management and the link between early warning and performance measurement. It offers a new idea on how performance measurement can be used as an effective early warning system and is intended to be primarily of use to project management practitioners and practically‐oriented academics who are interested in developing fresh insights into new approaches for better management of projects.

Discusses the results of evaluations of flood forecasting, warning and response systems in England, Wales, Scotland and Northern Ireland. Reveals that in England and Wales flood warning systems often underperform. Despite technical sophistication and their elevation to high priority in central government′s flood defence strategy, arrangements for flood warnings are now under considerable stress because of lack of agreement over organizational roles and responsibilities. Legal ambiguities, funding difficulties and ideological positions lie behind these problems. Flood warning systems are developing in Scotland, and there is now a “fledgling” system in Northern Ireland, but both lag behind England and Wales. Examines implications for the future.

The presentation of in-vehicle warnings information at risky driving scenarios is aimed to improve the collision avoidance ability of drivers. Existing studies have found that driver’s collision avoidance performance is affected by both warning information and driver’s workload. However, whether moderation and mediation effects exist among warning information, driver’s cognition, behavior and risky avoidance performance is unclear.

This purpose of this study is to examine whether the warning information type modifies the relationship between the forward collision risk and collision avoidance behavior. A driving simulator experiment was conducted with waring and command information.

Results of 30 participants indicated that command information improves collision avoidance behavior more than notification warning under the forward collision risky driving scenario. The primary reason for this is that collision avoidance behavior can be negatively affected by the forward collision risk. At the same time, command information can weaken this negative effect. Moreover, improved collision avoidance behavior can be achieved through increasing drivers’ mental workload.

The proposed model provides a comprehensive understanding of the factors influencing collision avoidance behavior, thus contributing to improved in-vehicle information system design.

The significant moderation effects evoke the fact that information types and mental workloads are critical in improving drivers’ collision avoidance ability. Through further calibration with larger sample size, the proposed structural model can be used to predict the effect of in-vehicle warnings in different risky driving scenarios.

The 2004 Boxing Day tsunami prompted global efforts to develop end-to-end multi-hazard warning systems. Taking this event as a starting point, and drawing on experiences from the following advancement of the Indonesian tsunami early warning system, this paper aims to highlight the importance of paying attention to human factors and the perceptions and behaviors of end recipients when trying to design efficient early warning systems.

The study is a viewpoint where theoretical frameworks for the design of efficient early warning systems are used as backdrop to an extensive review and analysis of secondary data, including scientific papers and newspaper articles.

The paper presents what an end-to-end warning system means, explores process problems related to perception and communication and concludes with views and recommendations toward more inclusive early warnings.

Research and practice related to early warning systems have traditionally had a strong focus on technological elements whilst the target groups of early warnings (i.e. communities) have received far less attention and resources. This paper focuses on the human dimension of warning systems and uses a real case to exemplify how efficient warning systems not only require a sound scientific and technological basis, but also depend on the awareness, trust and will of the people they aim to protect.

Sensing- and warning-based technologies are widely used in the construction industry for occupational health and safety (OHS) monitoring and management. A comprehensive understanding of the different types and specific research topics related to the application of sensing- and warning-based technologies is essential to improve OHS in the construction industry. The purpose of this paper is to examine the current trends, different types and research topics related to the applications of sensing- and warning-based technology for improving OHS through the analysis of articles published between 1996 and 2017 (years inclusive).

A standardized three-step screening and data extraction method was used. A total of 87 articles met the inclusion criteria.

The annual publication trends and relative contributions of individual journals were discussed. Additionally, this review discusses the current trends of different types of sensing- and warning-based technology applications for improving OHS in the industry, six relevant research topics, four major research gaps and future research directions.

Overall, this review may serve as a spur for researchers and practitioners to extend sensing- and warning-based technology applications to improve OHS in the construction industry.