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It evaluated the seismic vulnerability based on fewer factors by presenting the effectiveness of seismic and structural parameters. The proposed method first demonstrated the effect of earthquake ground motion inputs on predicting the slight, moderate, extensive and collapse limit states and confirmed the method’s efficiency. The fragility curves illustrated with the approach of the present study are compared with the traditional techniques, such as analytical methods.

Based on the different macro- and micro-structural characteristics and the earthquake records, achieving a certain relation from regression analysis using artificial neural networks (ANNs) is difficult. With this background in mind, the present study aimed to compare the proposed model of the considered bridge with the analytical and ANN results. After statistical analysis and estimation of the most effective factors in predicting responses from the proposed approach, two-parameter two- and three-dimensional fragility curves are extracted.

Due to the structural differences between horizontally curved bridges, the methodology does not require any classification of bridge classes to predict responses. For a specific L/R of the bridge, the parameters cumulative absolute velocity (CAV) and Sa (T1) can provide a good estimate of the seismic fragility curves, and the proposed approach with less parameter assignment also leads to good results. With less computational effort, fragility curves can be illustrated.

The proposed method demonstrated the ability to accurately estimate the occurrence and non-occurrence limit states while maintaining a low computational cost and the derivation of a curved bridge’s seismic fragility curve.

The purpose of this research is as follows: DPP-BOH-PVA has been synthesized from 1,1′:3′,1″-terphenyl-5'-boronic acid (DPP-OH) and polyvinyl alcohol (PVA). The afterglow lifetime of DPP-BOH-PVA was studied by changing contents of DPP-OH (1, 2 and 4 Wt.%). These films were characterized with Fourier transform infrared, X-ray diffraction as structural analysis and DSC as thermal analysis. Afterglow lifetimes were evaluated as time-resolved emission decay profile analysis. Fiber films of DPP-BOH-PVA-2-E have been prepared by electrospinning method with the diameter of 5 μm and afterglow life time of 2.1 s (@ 535 nm) under ambient conditions. Stimulus responsive properties with afterglow emission for fiber film were investigated.

During the synthesis of the polymer, modification was carried out using DPP-OH/PVA with a molar ratio of 1/4, under an alkalinity medium with ammonium hydroxide and with a temperature of 80°C.

XRD results indicate that DPP-BOH-PVA film had high crystallinity, which is crucial for preparing organic room temperature phosphorescence (RTP) materials.

The reaction mixture must be stirred continuously. Temperature should be controlled to prevent the rapid evaporation of ammonium hydroxide.

This study provides technical information for the synthesis of multidimensional stimulation response RTP micron fiber thin film. The electrospinning technology may also promote the applications of the large areas of RTP films.

This resin will be used for the multidimensional stimulation response RTP fiber thin film.

The diameter of fiber film of PP-BOH-PVA-2-E by electrospinning method was in the range of 5 μm, and its afterglow lifetime decayed to be 2.1 s.

This paper aims to confront the rising threat of deepfake videos, focusing on the limited research on deepfake detection strategies among seniors. The study thus investigates seniors’ video credibility conceptualizations and identifies their deepfake detection strategies.

This study employed semi-structured interviews with 20 seniors aged 55 to 70. Areas covered include their perceptions of video information credibility and identification strategies undertaken. Qualitative content analysis was conducted to interpret interview responses.

Seniors emphasized the importance of objectivity, trustworthiness, believability, reliability and truthfulness in terms of video credibility. Regarding strategies for assessing video credibility, seniors employed five categories: character appearance, non-human visuals, audio, personal knowledge and external sources.

This study contributes to the literature on human-oriented deepfake detection strategies by uncovering diverse methods employed by seniors. It enhances the understanding of how individuals assess video credibility in the context of deepfakes. Furthermore, this study offers practical and applicable strategies for real-world deepfake detection.

This paper aims to propose a set of metamodels applicable to the architecture modeling of air traffic management systems|air traffic management system (ATMS) under the UAF methodology. The designing of metamodels also needs to meet modeling requirements for the introduction of new supersonic airliners into the ATMS.

In order to complete the designing of metamodels and the architecture modeling work in the case study, the GOPPRR method and the M0–M3 modeling framework are used in this paper. The design and modeling work carried out in this paper was done in the multi-architecture modeling tool Airdraw.

In this paper, the set of metamodels applicable to the architecture modeling of ATMS under the UAF methodology was proposed, which has a quantity of 102 object metamodels, eight point metamodels, 98 property metamodels, 41 relationship metamodels, 36 role metamodels and 65 graph metamodels.

The metamodel design proposed in this thesis allows for architectural modeling of the ATMS. Comparing with the traditional method of system engineering, which uses files to define, the model-based ATMS architecture can be updated for different ATMS and different aircraft types by modifying the parameters of the corresponding views or adding relevant supplementary model views in the architecture model library, which greatly improves the compatibility and modifiability of the system definition.

Amid rising concerns over unhealthy dietary habits and their impact on public health, this study aims to explore the role of avatars in promoting healthier eating and enhancing customer satisfaction in restaurants. By leveraging the theory of planned behavior (TPB) and nudge theory, this research sought to gain insights into consumer behavior and assess how digital innovations can encourage healthier food choices.

This study recruited 672 participants in the USA. Participants viewed a video featuring an avatar that informed them about available healthy food options, simulating a restaurant ordering scenario. Following the video, participants completed comprehensive online surveys. The collected data was analyzed using partial least squares structural equation modeling to assess the effectiveness and implications of the intervention.

The findings revealed that health consciousness, environmental awareness, social norms and perceived behavioral control significantly influence dietary habits. Restaurant health initiatives and avatar persuasiveness were found to encourage healthier food choices, improve customer satisfaction and loyalty and enhance electronic word-of-mouth. The study confirmed that avatars equipped with attributes such as competence, warmth, trustworthiness and credibility can be an effective digital nudge for consumers toward healthier dietary decisions.

This study’s originality lies in its integration of TPB and nudge theory, bridging the gap between individual psychological factors and external cues. This comprehensive framework provides valuable insights for restaurant managers, artificial intelligence developers and policymakers, offering practical strategies to promote healthier eating and enhance customer experiences through digital innovation.

鉴于公众对不健康饮食习惯及其对公共健康影响的日益关注, 本研究旨在探索虚拟形象在促进更健康饮食和提升餐厅顾客满意度中的作用。通过利用计划行为理论（TPB）和劝导理论（Nudge Theory）, 本研究试图深入了解消费者行为, 并评估数字创新如何鼓励更健康的食品选择。

本研究在美国招募了672名参与者。参与者观看了一个展示虚拟形象的视频, 该虚拟形象向他们介绍了可供选择的健康食品选项, 模拟了餐厅点餐场景。观看视频后, 参与者完成了全面的在线调查。收集的数据通过偏最小二乘结构方程模型（PLS-SEM）分析, 以评估干预的有效性和影响。

研究发现, 健康意识、环境意识、社会规范和感知行为控制显著影响饮食习惯。餐厅健康倡议和虚拟形象的说服力被发现能够鼓励更健康的食品选择, 提高顾客满意度和忠诚度, 并增强电子口碑。研究证实, 具备能力、温暖、可信度和信誉等属性的虚拟形象可以成为有效的数字劝导工具, 引导消费者作出更健康的饮食决策。

本研究的原创性在于它将计划行为理论和劝导理论结合起来, 填补了个体心理因素和外部线索之间的差距。这一综合框架为餐厅经理、人工智能开发者和政策制定者提供了宝贵的洞见, 提供了推动更健康饮食和通过数字创新增强顾客体验的实用策略。

En medio de la creciente preocupación por los hábitos alimentarios poco saludables y su impacto en la salud pública, este estudio pretende explorar el papel de los avatares en la promoción de una alimentación más saludable y la mejora de la satisfacción del cliente en los restaurantes. Aprovechando la Teoría del Comportamiento Planificado (TPB) y la Teoría del Impulso, esta investigación trata de profundizar en el comportamiento del consumidor y evalúa cómo las innovaciones digitales pueden fomentar la elección de alimentos más saludables.

El estudio reclutó a 672 participantes en Estados Unidos. Los participantes visionaron un vídeo en el que un avatar les informaba sobre las opciones de comida saludable disponible, simulando una situación en la que solicitaban comida en un restaurante. Después del vídeo, los participantes rellenaron unas exhaustivas encuestas en línea. Los datos recogidos se analizaron mediante un modelo de ecuaciones estructurales por mínimos cuadrados parciales para evaluar la eficacia y las implicaciones de la intervención.

Los resultados revelaron que la conciencia saludable, la conciencia medioambiental, las normas sociales y el control conductual percibido influyen significativamente en los hábitos alimentarios. Se comprobó que las iniciativas relacionadas con la salud en los restaurantes y la capacidad de persuasión de los avatares fomentan la elección de alimentos más sanos, mejoran la satisfacción y la fidelidad de los clientes y potencian el boca a boca electrónico. El estudio confirmó que los avatares dotados de atributos como competencia, calidez, fiabilidad y credibilidad pueden ser un estímulo digital eficaz para que los consumidores tomen decisiones dietéticas más saludables.

La originalidad de este estudio radica en la integración de la TPB y la Teoría de los Estímulos, que tiende un puente entre los factores psicológicos individuales y las señales externas. Este marco integral aporta valiosas ideas a los gestores de restaurantes, desarrolladores de IA y responsables políticos, ofreciendo estrategias prácticas para promover una alimentación más sana y mejorar las experiencias de los clientes a través de la innovación digital.

By comparing and contrasting the two scenarios of power producers investing in renewable energy and electricity sellers investing in renewable energy, we explore the conditions under which profit growth and carbon emission reduction can be realized, and provide a theoretical basis for decision-making on renewable energy investment by electric power companies as well as for government policy formulation.

This paper constructs a game model of a grid supply chain consisting of a leader generator and a follower seller in the context of the C&T mechanism, considering two scenarios in which the generator and the seller invest in renewable energy. Conclusions are drawn by comparing and analyzing the equilibrium solutions in different scenarios.

The scenario where electricity sellers invest in renewable energy exhibits a higher investment volume compared to the scenario involving power generators. In scenarios where power producers invest in renewable energy, electricity sellers achieve lower profits than power generators, while scenarios with electricity seller' investments yield higher profits for them. Increasing the cost coefficient of renewable energy investment reduces investment volume, electricity prices and electricity demand, leading to decreased profits for electricity seller but increased profits for power generator. A rise in the preference coefficient for renewable energy results in increased profits for electricity seller but decreased profits for power generator.

Addressing a literature gap in the context of low carbon, this study examines the investment scenario of electricity sellers in low carbon technologies, complementing existing research focused on power generators and consumers. The findings enrich knowledge in low carbon investment. By analyzing the investment decisions of both power producers and electricity sellers, this study explores the practical implications of renewable energy investments on the decision-making and operational dynamics of power supply chain enterprises. It sheds light on their profitability and investment strategies.

This paper aims to study the impact of the interaction effects between live-streaming marketing and clothing type on consumers' intention to purchase clothing, and the mediating effect of internalization and identification on the relationship between them.

This paper conducts a scenario experiment to 486 consumers who had experience in purchasing clothing on the live-streaming platform and employs the analysis of variance, structural equation model and multivariate regression model.

Our findings reveal that professional live-streaming marketing (PLSM) can better stimulate consumers' intention to purchase formal clothing than entertainment live-streaming marketing (ELSM) does. Compared with PLSM, ELSM can better stimulate consumers' intention to purchase casual clothing. When PLSM promotes formal clothing, it triggers the internalization mechanism of consumers, so as to improve their purchase intention. When ELSM promotes casual clothing, it triggers consumers' identification mechanism, so as to improve their purchase intention.

This paper helps to identify the differences in the impact of different types of live-streaming marketing on consumers' intention to purchase different types of clothing, as well as the mediating role of internalization and identification mechanisms. This paper provides a theoretical reference for clothing firms to strategically select the appropriate type of live-streaming marketing.

The emergence of live streaming commerce has injected promising impetus into rural development and attracted many rural streamers. This study aims to explore the influencing factors of rural streamers’ engagement intentions to help promote the sustainable development of rural live streaming commerce.

Grounded in the extended valence framework, this research employs a mixed-methods approach encompassing both qualitative and quantitative methodologies. In the qualitative phase, the authors conduct in-depth interviews with 15 rural streamers, employing data coding techniques to uncover underlying factors. Subsequently, in the quantitative phase, the authors analyze survey data from 282 rural streamers, subjecting hypotheses to validation through structural equation modeling.

The findings derived from the analysis of both interviews and questionnaires reveal that several platform qualities, including platform rural-aiding support, perceived effectiveness of dispute resolution, perceived interactivity and platform reputation, have a positive effect on trust in the platform and validate the extended valence framework in understanding rural streamers’ live streaming intention. In addition, ties with customers have a moderating effect. Specifically, the stronger the ties with customers, the stronger the positive effect of perceived benefits and the weaker the positive effect of trust in the platform on live streaming intention will be.

This study contributes to the rural live streaming commerce literature and trust research from the sellers’ perspective and provides practical implications for policymakers and live streaming platform managers on enhancing rural streamers’ participation.

This study reduces carbon emission in logistics distribution to realize the low-carbon site optimization for a cold chain logistics distribution center problem.

This study involves cooling, commodity damage and carbon emissions and establishes the site selection model of low-carbon cold chain logistics distribution center aiming at minimizing total cost, and grey wolf optimization algorithm is used to improve the artificial fish swarm algorithm to solve a cold chain logistics distribution center problem.

The optimization results and stability of the improved algorithm are significantly improved and compared with other intelligent algorithms. The result is confirmed to use the Beijing-Tianjin-Hebei region site selection. This study reduces composite cost of cold chain logistics and reduces damage to environment to provide a new idea for developing cold chain logistics.

This study contributes to propose an optimization model of low-carbon cold chain logistics site by considering various factors affecting cold chain products and converting carbon emissions into costs. Prior studies are lacking to take carbon emissions into account in the logistics process. The main trend of current economic development is low-carbon and the logistics distribution is an energy consumption and high carbon emissions.

Existing research has shown the role of social media in facilitating general protest participation. However, there is a noticeable gap in understanding the dynamics related to explicitly unlawful behaviors during protests, which have become increasingly prominent in recent times. Drawing upon the communication mediation model (O-S-O-R model), this study proposes a moderated mediation model to delineate specific mechanisms under which social media use influences individuals' support for unlawful behaviors in protests.

A survey of 1,121 Hong Kong residents was conducted in the context of the 2019 Hong Kong Anti-Extradition Law Amendment Bill Movement to test the theoretical model.

Obtaining political information on social media has a dual effect on support for unlawful behaviors in protests. On one hand, social media use increases individuals' political knowledge, which is reinforced by frequent political discussions on social media. This enhanced political knowledge tends to reduce the likelihood of supporting unlawful behaviors in protests. On the other hand, acquiring political information on social media can also generate increased anger toward politics, potentially leading to a more supportive attitude toward unlawful behaviors in protests.

This study contributes to the expanding field of research on digital activism by revealing the intricate mechanisms by which social media usage shapes support for unlawful behaviors in protests. It also expands our understanding of explicit unlawful behaviors within protests as a distinct form of political behavior.