Search Results (43)

Extreme heat poses growing health risks in tropical regions, yet public perception of this threat remains understudied in the Caribbean. This study examines how residents in Puerto Rico perceived heat-related health risks and how these perceptions relate to vulnerability and protective behaviors during the extreme heat events of the summer of 2020. We conducted a cross-sectional telephone survey of 500 adults across metropolitan and non-metropolitan areas of Puerto Rico, using stratified probability sampling. The questionnaire assessed heat risk perception, sociodemographic characteristics, health status, prior heat exposure, and heat-related behaviors. While most participants expressed concern about climate change and high temperatures, fewer than half perceived heat as a high level of personal health risk. Higher levels of risk perception were significantly associated with being male, aged 50–64, unemployed, and in fair health, having multiple chronic conditions, and prior experience with heat-related symptoms. Those with symptoms were nearly five times more likely to report high levels of risk perception (OR = 4.94, 95% CI: 2.93–8.34). In contrast, older adults (65+), despite their higher level of vulnerability, reported lower levels of risk perception and fewer symptoms. Nighttime heat exposure was widespread and strongly associated with heat-related symptoms. Common coping strategies included the use of fans and air conditioning, though economic constraints and infrastructure instability limited access. The findings highlight the disparity between actual and perceived vulnerability, particularly among older adults. Public health strategies should focus on risk communication tailored to vulnerable groups and address barriers to heat adaptation. Strengthening heat resilience in Puerto Rico requires improved infrastructure, equitable access to cooling, and targeted outreach. Full article

This study examines the psychological mechanisms through which BTS’s perceived star attributes—expertise, authenticity, likability, and similarity—influence fan loyalty within fandom-driven tourism. Anchored in activity theory and content theory of motivation, the proposed model identifies psychological need fulfillment and emotional satisfaction as sequential mediators linking celebrity perception to loyalty behaviors. Data were obtained from 916 BTS fans across six English-speaking countries via a structured online survey. To test the hypothesized relationships, Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed. Results demonstrate that perceived star attributes significantly enhance psychological need fulfillment, which subsequently predicts emotional satisfaction and loyalty. Additionally, the attributes exert direct effects on emotional satisfaction, supporting both reflective and intuitive engagement pathways. All hypothesized paths were statistically significant, and the model exhibited strong overall fit (SRMR = 0.039; NFI = 0.875). Theoretically, this study advances loyalty research by foregrounding the roles of symbolic consumption, emotional resonance, and identity-based alignment in global fandom contexts. Practically, the findings offer insights for tourism marketers, destination planners, and entertainment brands seeking to design emotionally immersive, narrative-rich tourism experiences. Recommendations are provided for developing BTS-themed content aligned with fans’ identity motivations to foster sustained emotional engagement and destination loyalty. Full article

Blockchain technology is reshaping the sports industry by enhancing transparency, data security, and fan engagement through applications such as smart contracts, tokenized sponsorships, and decentralized ticketing. This study investigates blockchain adoption in Romanian team sports, specifically football and basketball, through a comparative analysis based on a survey of 293 sports professionals (213 from football and 80 from basketball). Using structural equation modeling (SEM) with SmartPLS and cluster analysis in SPSS, the study explores the perceived benefits of blockchain and its relationship with athlete performance. The findings reveal distinct adoption patterns: football shows higher use of blockchain in ticketing and fan engagement, while basketball leads in performance analytics and financial support mechanisms. Statistically significant differences were confirmed through MANOVA, and clustering revealed varied stakeholder perceptions across professional roles. Benchmarking against sectors like finance and healthcare highlights transferable best practices for blockchain integration in sports. Full article

Personal Comfort Systems (PCS) have emerged as a flexible alternative to address the diversity of environmental perceptions in office environments. Unlike conventional HVAC systems, PCSs allow users to improve their satisfaction and comfort by exercising individualized control over their immediate environment without interfering with others around them. This study evaluated the use of machine learning models generated by H2O AutoML to predict the use of three PCSs in four office buildings with effective occupancy. These were a thermal wristband, a desk fan, and an adjustable lamp. Data collected through environmental sensors, perception surveys, and spatial and personal attributes were used. Synthetic data augmentation and automated variable selection were also used to optimize the models’ performance. The predictive models had a robust performance, with R² values in the test set of 0.86 for the wristband, 0.84 for the fan, and 0.52 for the lamp. The most influential variables included the BMI, CO₂ level, and thermal satisfaction, highlighting the importance of physiological and subjective factors. The results confirm that the models allow anticipating the use of PCS with high precision in most cases, laying the foundations for the future implementation of user-oriented adaptive systems. This preliminary approach contributes to the design of healthier, more personalized, and more energy-efficient work environments. Full article

This qualitative research explores the intersection of social media, personal branding, and perceived authenticity in sports figures, focusing on Deion Sanders’s digital presence as head football coach at the University of Colorado. Two interrelated studies examine how Sanders manages his authenticity on social media and how audiences perceive his authenticity. Study 1 employs a six-factor framework applied to eight focus groups to understand what factors social media audiences consider most important in developing Sanders’s perceived authenticity as a digital content creator. Study 2 utilizes a two-factor model of authenticity management to examine Sanders’s personal social media content during his inaugural season as CU’s head coach. The research incorporates a spatial perspective from sport sociology. This approach examines how Sanders’s social media activity creates and shapes virtual spaces where interaction and identity formation occur. Findings reveal that while Sanders is generally perceived as authentic, digital charisma emerged as the most significant factor in constructing his perceived authenticity. The study contributes to understanding the evolving nature of authenticity in digital spaces and the role of digital charisma in personal branding for public figures balancing multiple roles. Full article

Due to accelerated urbanization, modern urban residents are facing increasing life pressures. Many citizens are experiencing situational aversion in daily commuting, and the deterioration in the traffic environment has led to psychological distress of varying degrees among urban dwellers. Cyclists, who account for about 7% of urban commuters, lack a sense of belonging in the urban space and experience significant deficiencies in the corresponding urban infrastructure, which causes more people to face significant barriers to choosing cycling as a mode of transportation. To address the aforementioned issues, this study proposes a bionic intelligent interaction helmet (BIIH) designed and validated based on the principles of bionics, which has undergone morphological design and structural validation. Constructed around the STM32-embedded development board, the BIIH is an integrated smart cycling helmet engineered to perceive environmental conditions and enable both human–machine interactions and environment–machine interactions. The system incorporates an array of sophisticated electronic components, including temperature and humidity sensors; ultrasonic sensors; ambient light sensors; voice recognition modules; cooling fans; LED indicators; and OLED displays. Additionally, the device is equipped with a mobile power supply, enhancing its portability and ensuring operational efficacy under dynamic conditions. Compared with conventional helmets designed for analogous purposes, the BIIH offers four distinct advantages. Firstly, it enhances the wearer’s environmental perception, thereby improving safety during operation. Secondly, it incorporates a real-time interaction function that optimizes the cycling experience while mitigating psychological stress. Thirdly, validated through bionic design principles, the BIIH exhibits increased specific stiffness, enhancing its structural integrity. Finally, the device’s integrated power and storage capabilities render it portable, autonomous, and adaptable, facilitating iterative improvements and fostering self-sustained development. Collectively, these features establish the BIIH as a methodological and technical foundation for exploring novel research scenarios and prospective applications. Full article

Motorsports tourism has a significant impact on host communities, especially when they are small communities. This research aims to segment the resident population of a very small rural municipality, Obejo, before the celebration of the Sierra Morena Rally in the province of Cordoba, Spain. The study is based on the principles of social exchange theory (SET) and the triple bottom line (TBL). In addition, it follows calls from the existing academic literature to explore a fourth dimension of impact perception, related to inclusion from the point of view of gender, age, and functional diversity. exploratory factor analysis (EFA) and non-hierarchical cluster analysis were used on a sample of 281 residents. A structure of four dimensions of impact perception is obtained: economic, social, environmental, and inclusive. Together, they explain just over 80% of the total variance. Three population segments are defined: motor enthusiasts, environmentally conscious fans, and admitted critics. This study underlines the need to expand the TBL framework with an inclusive dimension in motorsports tourism, emphasizing gender equality, intergenerational participation and functional diversity to foster more sustainable and socially cohesive events in rural areas. Full article

Existing intelligent fault diagnosis methods have been widely developed and proven to be effective in monitoring the operating status of key mechanical components. However, centrifugal fans, as important equipment in energy and manufacturing industries, have been used for a long time in complex and harsh environments such as boiler plants and gas turbines. Therefore, the vibration signals they generate show complex and diverse characteristics, which brings great challenges to the monitoring of centrifugal fan operation status. To solve this problem, this paper proposes a centrifugal fan blade fault diagnosis method based on a modulational depthwise convolution (DWconv)–one-dimensional convolution neural network (MDC-1DCNN). Specifically, firstly, a convolutional modulation module (CMM) with strong local perception and global modeling capability is designed by drawing on the Transformer self-attention mechanism and global context modeling idea. Second, multiple DWconv layers of different sizes are introduced to capture high-frequency shocks and low-frequency fluctuation information of different frequencies and durations in the signal. Next, a DWconv layer of size 11 is embedded in the multilayer perceptron to enhance spatial information representation while saving computational resources. Finally, to verify the effectiveness of the method, this paper simulates and analyzes the actual working state of centrifugal fan blades, constructs a simulation dataset, and builds a centrifugal fan experimental bench to obtain a real dataset. The experimental results show that the MDC-1DCNN framework significantly outperforms the existing methods in both simulation and experimental bench datasets, fully proving its versatility and effectiveness in centrifugal fan blade fault diagnosis. Full article

The escalating summer heat in the Middle East and Northern Africa (MENA) region, particularly in Bahrain, poses a significant threat to human health, prompting the use of water mist systems for immediate heat stress relief and heat stroke treatment. Although these systems are known for their rapid cooling effects, the impact of varying water temperatures on their efficiency is not well understood. This research addressed this gap by investigating the effects of different water temperatures on cooling performance and user comfort in a semi-outdoor environment in Bahrain. Field experiments, comparing mist fan system (MFS) zones with non-misted areas, were conducted alongside user surveys to assess perceived thermal comfort. The findings revealed that lower water temperatures significantly enhanced cooling, with a 7.7 °C water temperature achieving a 4 °C temperature reduction and improving perceived comfort. The MFS effectively shifted participant perceptions from “Hot” or “Slightly Warm” to “Natural” or “Slightly Cool”, confirming its rapid heat mitigation capabilities. Notably, 54.5% of participants preferred the system using the coldest water, citing immediate relief. Despite the substantial cooling benefits, achieving standard thermal comfort during peak heat remained challenging. Future research should explore nozzle optimization, wind effects, water usage, solar-powered system efficiency, and the impact of clothing on thermal comfort. Full article

This study explored how fans’ perceptions of sponsor participation in environmental, social, and governance (ESG) activities influence attitudes toward the sponsor, sponsor image, electronic word of mouth (eWOM), and purchase intentions. Limited research has focused on the interactions between sports sponsorship and ESG activities. This study filled this research gap by considering the case of the Rakuten Monkeys, a professional baseball team in Taiwan, and its sponsors. Grounded in the theory of planned behavior, this study investigated how fans’ perceptions of sponsor participation in ESG initiatives affect their purchase intentions through sponsor attitudes, sponsor image, and eWOM. A total of 800 Rakuten Monkeys fans were recruited for this study, and the study hypotheses were tested using structural equation modeling. The results indicate that all investigated paths were significant. That is, fans’ perceptions of sponsor participation in ESG activities significantly enhance their attitudes toward the sponsor and sponsor image, which in turn positively influence their eWOM and purchase intentions. This study has theoretical and practical implications for enhancing brand image and consumer purchase intentions through ESG activities. The study contributes valuable insights that can be used by sports sponsors for developing marketing strategies. Full article

The global VTuber market is experiencing rapid growth, with VTubers extending beyond mere content creators to be utilized in various fields such as social interaction, public relations, and health. VTubers have the potential to expand the existing content market and contribute to increasing economic and public value. This study aims to investigate the perception of VTubers in South Korea and to provide insights that can contribute to the global activation of the VTuber entertainment industry. For this purpose, unstructured data on VTubers from the past three years, during which interest in VTubers has significantly grown in South Korea, was collected. A total of 57,891 samples were gathered from Naver, Daum, and Google, of which 50 highly relevant data points between VTubers and users were selected for analysis. First, key terms such as ‘Broadcast’, ‘YouTube’, ‘Live’, ‘Game’, ‘Youtuber’, ‘Japan’, ‘Character’, ‘Video’, ‘Sing’, ‘Virtual’, ‘Woowakgood’, ‘Fan’, ‘Idol’, ‘Korea’, ‘Twitch’, ‘IsegyeIdol’, ‘Communication’, ‘Worldview’, ‘VTuberIndustry’, ‘Contents’, ‘AfricaTV’, ‘Nijisanji’, and ‘Streamer’ were extracted. Second, CONCOR analysis revealed four clusters: ‘Famous VTubers’, ‘Features of VTubers’, ‘VTuber Industry’, and ‘VTuber Platforms’. Based on these findings, the study offers various academic and practical implications regarding VTubers in South Korea and explores the potential for global growth in the VTuber industry. Full article

With the advancement of technology, unmanned ground vehicles (UGVs) have shown increasing application value in various tasks, such as food delivery and cleaning. A key capability of UGVs is obstacle detection, which is essential for avoiding collisions during movement. Current mainstream methods use point cloud information from onboard sensors, such as light detection and ranging (LiDAR) and depth cameras, for obstacle perception. However, the substantial volume of point clouds generated by these sensors, coupled with the presence of noise, poses significant challenges for efficient obstacle detection. Therefore, this paper presents a fast obstacle detection algorithm designed to ensure the safe operation of UGVs. Building on multi-sensor point cloud fusion, an efficient ground segmentation algorithm based on multi-plane fitting and plane combination is proposed in order to prevent them from being considered as obstacles. Additionally, instead of point cloud clustering, a vertical projection method is used to count the distribution of the potential obstacle points through converting the point cloud to a 2D polar coordinate system. Points in the fan-shaped area with a density lower than a certain threshold will be considered as noise. To verify the effectiveness of the proposed algorithm, a cleaning UGV equipped with one LiDAR sensor and four depth cameras is used to test the performance of obstacle detection in various environments. Several experiments have demonstrated the effectiveness and real-time capability of the proposed algorithm. The experimental results show that the proposed algorithm achieves an over 90% detection rate within a 20 m sensing area and has an average processing time of just 14.1 ms per frame. Full article

Expanding waste-to-energy (WtE) facilities is difficult, and with tightening incineration regulations, improvements in WtE facility operations are required to dispose of waste that is increasing by an average of 4.8% annually. To achieve this, an intelligent combustion control (ICC) system was studied using digital technologies such as the Internet of Things and artificial intelligence to improve the operation of WtE facilities. The ICC system in this study is composed of three modules: perception, decision, and control. Perception: collecting and visualizing digital data on the operating status of WtE facilities; Decision: using AI to propose optimal operation methods; Control: automatically controlling the WtE facility according to the AI-suggested optimization methods. The ICC system was applied to the “G” WtE facility, a solid waste WtE facility operating in Gyeonggi province, Republic of Korea, and the digital data collected over six months showed high quality, with low delay and a data loss rate of only 0.12%. Additionally, in January 2024, the ICC system was used to automatically control the second forced draft fan and induced draft fan over a four-day period. As a result, the incinerator flue gas temperature decreased by 0.66%, steam flow rate improved by 2.41%, power generation increased by 3.09%, CO emissions were reduced by 60.72%, and NOx emissions decreased by 7.33%. Future research will expand the ICC system to include the automatic control of the first forced draft fan and the operation time of the stoker. Full article

Personal Comfort Systems (PCSs) have emerged as an innovative solution to address variable individual conditions that traditional comfort models excluded. This study investigates the impact of the simultaneous application and use of three PCSs in real office environments on an occupant’s thermal, light, and air quality perception and seeks to understand different environmental stimuli behind personal actions and behaviors. It uses qualitative and quantitative monitoring of specific environmental conditions and individual actions of 72 participants in four office buildings in different climatic zones of Chile in summer and winter. The PCSs tested differ in their costs, technological level, usability, and portability. The results show that 85.5% improved their perceived comfort by using the PCSs, although not from simultaneous use, but rather from the use of one system over another. The desk fan stands out as having the highest acceptance and utilization rate. However, certain environmental conditions cause opposite actions: limited lighting control or little daylight causes the fan to be turned on. The present study’s data could contribute to a new environmental comfort model for shared office spaces, fostering significant improvements in occupant satisfaction and energy efficiency. This practical and scientific research is of interest to architects, designers, and stakeholders from the construction production field. Full article

Rising global temperatures have increased the need for research into human adaptability and comfort in buildings. To reduce comfort-related energy demands, low-energy-consumption alternatives for space cooling, such as personal environmental control systems (PECS), are being investigated. The implementation of PECS in office buildings is still underway, and little is known about how occupants’ expectations can influence their satisfaction with PECS and indoor environmental quality. This study examines the influence of tailored information and occupants’ comfort expectations on their thermal perceptions and satisfaction with a personal ceiling fan. Seventy-six participants completed an online questionnaire and attended a half-day session at 30 °C in a climate chamber in Germany. A manipulation technique to activate personal norms was used to test the influence of information on expectations. Results indicated higher reported thermal comfort in participants with more positive thermal expectations, regardless of their expectations of the building systems. These effects were largely moderated by personal norms, indicating the importance of activating normative motivations to increase thermal comfort. Occupants with negative expectations improved their perceptions of the fan when making personal adjustments to stay comfortable. However, this effect was not moderated by personal norms. Practical implications focus on manipulating occupants’ comfort expectations, e.g., by providing occupants with normative messages and individual control, to achieve greater comfort and acceptance of personal building controls in naturally ventilated buildings. Full article