Search Results (26,299)

In the rapidly evolving platform economy, online platforms have emerged as pivotal providers of digital services to sellers. The paper investigates how online platforms optimize service strategies based on consumers’ purchase behavior, influencing sellers’ pricing and social welfare. Using a two-period Hotelling model and a cooperative game framework, we discover that the optimal service strategies of a platform with data collecting capabilities are collaborating with two sellers to offer to extend services to new consumers in the second period, maximizing profits for all sellers and platform. Applying Shapley value analysis, we determine the platform’s equitable service charge strategies. When sellers adopt behavior-based pricing (BBP), the pricing escalates in the first period, and the platform’s optimal service strategies also enhance the pricing of sellers. However, in the second period, BBP intensifies competition, leading to generally lower pricing. Our findings suggest that optimal pricing in the second period for new consumers should increase with enhanced quality perception, which is provided by the platform’s digital services and heightened by consumers’ privacy concerns, while decreasing for regular consumers. Lastly, we offer policy recommendations, exploring optimal regulatory scenarios—limiting or not limiting data collection—to maximize social welfare or consumer surplus, and the Mathematica software is used to identify distinct optimal policy intervals. Full article

The branding of cities through their historical and cultural assets has become a pivotal strategy in urban development and tourism. This study focuses on Erbil Citadel, a UNESCO World Heritage Site, and its potential as a brand for Erbil, a city with a rich historical backdrop and flourishing urban landscape. The study aimed to explore the perceptions of Erbil’s residents regarding the cultural significance of the Citadel and its potential as a city brand. A mixed-method survey questionnaire was conducted, collecting data from around 440 residents through both manual distribution around the Citadel and an online platform. The findings were analyzed using SPSS 23 to provide both descriptive and inferential statistical insights. The findings show that locals are well aware of the Citadel’s significance as a significant historical and cultural symbol of the city. The vast majority of participants acknowledged its unique visual attributes and their representation of the city’s cultural and historical identity. Additionally, the results showed that citizens’ perceptions of the Citadel as a good component of city branding were positively correlated with their level of cultural awareness. This study contributes to the growing body of literature on city branding and heritage sites by providing empirical evidence on the impact of residents’ cultural awareness on their perceptions of heritage sites as city brands. The results highlight how crucial cultural education and community involvement are to maximizing the branding potential of historic locations. Policymakers and urban planners may find the findings of the study useful in utilizing Erbil Citadel’s historical relevance to strengthen Erbil’s brand identity internationally. Full article

Visual Impact Assessment (VIA) is a critical tool in managing cultural heritage, evaluating the impacts of development and construction projects on the visual aspects of heritage values. However, VIA is often constrained by subjectivity, low public participation, and a lack of generalizability. This study aims to develop a methodological framework for a more objective and comprehensive assessment of visual impacts on cultural heritage. The study establishes criteria for indicators based on the value attributes of cultural heritage, develops an assessment indicator system, and integrates visual sensitivity assessment through multi-factor calculations with visual perception assessment using the AHP method and questionnaire surveys. This constructs an assessment framework that combines both objectivity and subjectivity. The Shangri-La Hotel East Building project at the World Heritage site of the West Lake Cultural Landscape of Hangzhou, China, is employed as a case study to empirically demonstrate the framework’s practicality and effectiveness. The results indicate that the Shangri-La East Building significantly impacts the attributes of the West Lake. The conclusion demonstrates that the indicator system, grounded in the attributes of cultural heritage, enhances the framework’s applicability across different contexts. The integrated assessment framework, which includes both a quantitative assessment of visual sensitivity and a public-participation-based assessment of visual perception, is shown to be effective in predicting the visual impacts of proposed projects on heritage values. The study also underscores the importance of Heritage Impact Assessment as a preliminary evaluation. Full article

Background/Objectives: Fibromyalgia (FM) affects up to 5% of the global population and is a leading cause of significant social and economic consequences. Higher health literacy leads to better understanding of treatment plans, improved self-care, and adherence to recommendations, enhancing overall quality of life. This study aims to determine whether different aspects of the disease are influenced by patients’ education level and literacy when applying the same therapy and to assess how patients’ perceptions of therapy outcomes vary over time based on their educational level. Methods: This study involved 140 fibromyalgia (FM) patients diagnosed using the 2016 ACR criteria, with 128 completing the study. Participants attended three visits over 28 weeks and were stratified into four groups based on educational level: Group 1—secondary school or less; Group 2—high school graduates; Group 3—college graduates; Group 4—university graduates. Patients were assigned to groups (n = 32, 32, 30, and 34, respectively) after the initial evaluation (T0). The treatment was assessed (T1) and followed up three months later (T2) to evaluate changes in functional status and quality of life. All patients underwent the same rehabilitation program, cognitive therapy, and kinesiotherapy. Results: Significant differences in disease impact on the patient’s life (FIQ total score) were observed between groups from the initial evaluation (p = 0.000). The overall FIQ score was notably affected by non-pharmacological therapy in patients with higher education. These differences continued to be significant even three months after the treatment ended (p = 0.000). Functional limitations were evident from the start (p = 0.000) and improved significantly post-treatment in patients with higher education (p = 0.000). However, subjective evaluations of disease impact (assessed by the first item of FIQ) did not consistently align with objective findings (hand grip strength). Functional limitations did not significantly differ in subjective evaluations (F1Q1) across educational levels (p = 0.045), and inverse correlations were noted between functional status and SF-12 well-being components. Conclusions: This study underscores that higher education enhances fibromyalgia management and functional outcomes, particularly when combined with non-pharmacological therapies. However, subjective perceptions may not always align with objective improvements, indicating that factors beyond education, such as personal and external influences, also impact disease management. Thus, improving health literacy through educational interventions could further benefit FM patients’ quality of life. Full article

The importance of growth mindset and teachers’ feedback has been widely recognised to improve the English language performance of students; however, the impact of growth mindset as a mediator is least explored. Therefore, the study aimed to empirically analyse the interrelationships between growth mindset and teachers’ feedback levels on secondary school students’ English as a Second Language (ESL) performance and to study the mediation effects of growth mindset in the relationships. The research model examined growth mindset along with four types of feedback. The levels of feedback include task, process, self-regulation and self-based feedback that teachers provide to improve the ESL performance of students. Survey questionnaires were administered to 301 secondary school students in Class 9 from two private schools in India. The data were analysed using PLS-SEM 4.0 software. The results indicated that the direct effect of feedback that emphasised process and self-regulation fosters a growth mindset in ESL students. Feedback levels focused on task, process, self-regulation, and growth mindset significantly impact ESL performance. Moreover, growth mindset mediated the relationships between process and self-regulation-focused feedback and ESL performance. However, no evidence supports the relationship between self-focused feedback, growth mindset, and ESL performance. The study concludes with implications and directions for future research. Full article

Ain’t I a Woman? This question was raised by activist and self-emancipated former slavewoman Sojourner Truth, who validly questioned the body politic of identity when contextualized to perceptions of female personhood. Essentially, what Truth challenged were presumptions about the standards set to revere female bodies through markers of genteel Whiteness, while the worth of embodied Blackness, precisely the beauty of Black women, is reviled. In this article, I seek to raise awareness about factors of patriarchy and societal ramifications. Patriarchy is a systematized phenomenology of norms privileging the male gaze. The White male gaze, particularly in strongholds of power, influences the body politic of communal identity. Black women tend to lean on their faith to embody strength, yet patriarchy also encumbers the gendered body politic in religious spheres. As a womanist scholar, my analysis considers the intricate roles that patriarchy holds in the cultural production of a genteel, pretty woman image, wherein the aura of Whiteness grounds a body politic that deems Blackness as other. Despite the influences of prevailing macrosystems, I propose a theoethic of self-love to push against negatively biased identity boundaries by affirming ways to embrace Black beauty with a subversive imperative to love oneself regardless. Full article

Self-driving cars are one of the main areas of research today, but it has to be acknowledged that the information from the sensors (the perceptron) is a huge amount of data, which is now unmanageable even when projected onto a single traffic junction. In the case of self-driving, the nodes have to be sequenced and organized according to the planned route. A self-driving car in Hungary would have to be able to interpret more than 70,000 traffic junctions to be able to drive all over the country. Besides the huge amount of data, another problem is the issue of validation and verification. For self-driving cars, this implies a level of complexity using traditional methods that calls into question the economics of the already existing system. Fuzzy Petri nets provide an alternative solution to both problems. They allow us to obtain a model that accurately describes the reliability of a node through its dynamics, which is essential in perception since the more reliable a node is, the smaller the deep learning mesh required. In this paper, we outline the analysis of a traffic node’s safety using Petri nets and fuzzy analysis to gain information on the reliability of the node, which is essential for the modeling of self-driving cars, due to the deep learning model of perception. The reliability of the dynamics of the node is determined by using the modified fuzzy Petri net procedure. The need for a fuzzy extension of the Petri net was developed by knowledge of real traffic databases. Full article

Background: Visual perceptual learning plays a crucial role in shaping our understanding of how the human brain integrates visual cues to construct coherent perceptual experiences. The visual system is continually challenged to integrate a multitude of visual cues, including form and motion, to create a unified representation of the surrounding visual scene. This process involves both the processing of local signals and their integration into a coherent global percept. Over the past several decades, researchers have explored the mechanisms underlying this integration, focusing on concepts such as internal noise and sampling efficiency, which pertain to local and global processing, respectively. Objectives and Methods: In this study, we investigated the influence of visual perceptual learning on non-directional motion processing using dynamic Glass patterns (GPs) and modified Random-Dot Kinematograms (mRDKs). We also explored the mechanisms of learning transfer to different stimuli and tasks. Specifically, we aimed to assess whether visual perceptual learning based on illusory directional motion, triggered by form and motion cues (dynamic GPs), transfers to stimuli that elicit comparable illusory motion, such as mRDKs. Additionally, we examined whether training on form and motion coherence thresholds improves internal noise filtering and sampling efficiency. Results: Our results revealed significant learning effects on the trained task, enhancing the perception of dynamic GPs. Furthermore, there was a substantial learning transfer to the non-trained stimulus (mRDKs) and partial transfer to a different task. The data also showed differences in coherence thresholds between dynamic GPs and mRDKs, with GPs showing lower coherence thresholds than mRDKs. Finally, an interaction between visual stimulus type and session for sampling efficiency revealed that the effect of training session on participants’ performance varied depending on the type of visual stimulus, with dynamic GPs being influenced differently than mRDKs. Conclusion: These findings highlight the complexity of perceptual learning and suggest that the transfer of learning effects may be influenced by the specific characteristics of both the training stimuli and tasks, providing valuable insights for future research in visual processing. Full article

In the Sahel region of West Africa, land degradation has raised concerns about the threat of desertification, leading to the establishment of the United Nations Convention to Combat Desertification (UNCCD) in 1994. Over time, the focus has shifted from simply combating desertification to a more comprehensive international program focused on preserving the health of our land by offsetting any damage with restoration efforts by 2030 to sustain ecosystem functions and services. This balancing process—which is in line with the Sustainable Development Goals (SDGs)—is known as Land Degradation Neutrality (LDN). We examine Land Degradation Neutrality (LDN) patterns, namely degradation and rehabilitation processes, by integrating participatory mapping with high-resolution satellite imagery with local stories, observations, historical records, and existing studies. The data elicited an understanding of the processes driving land degradation and adaptation strategies among three distinct ethnic groups of crop and livestock farmers in the village of Yallé in southern Burkina Faso. Some of these people were originally from this region, while others moved from places where the land was already degraded. Participants in the study had diverse experiences and perceptions of land degradation, its drivers, and adaptation strategies, which were influenced by their ethnicity, livelihood activities, and life experiences. These differences highlight the impact of cultural and socioeconomic factors on how people view land degradation, as well as the role of local knowledge in managing the environment. The study emphasizes the necessity of incorporating ethnoecological perspectives into projects focused on Land Degradation Neutrality (LDN) to better understand land degradation and improve land management. This integration can significantly contribute to strengthening global sustainability and community resilience. Full article

The perception of health risks can influence people’s health behaviors. However, in the context of modern consumer society, few people delve into in-depth discussions on health consumption as a form of health protection behavior. Inspired by the Health Belief Model and Protection Motivation Theory, this study interprets health consumption behavior as a new form of health protection behavior. A survey was conducted on a sample of Chinese youth (N = 885) to explore the mechanisms of action between health risk perception and health consumption behavior using structural equation modeling. The study found that: (1) health risk perception has a significant positive impact on the health consumption behavior of young people; (2) negative emotions and information seeking play mediating roles respectively in the mechanism of the impact of health risk perception on health consumption behavior; and (3) in addition to their individual mediating roles, negative emotions and information seeking behavior collectively play a chained mediation role in this process. Implications of these results, both theoretical and practical, are further discussed. Full article

Background: Sugar-sweetened beverages (SSBs) account for a significant proportion of sugar in the diet of children and are directly associated with obesity in this group. While there have been many studies on adolescent SSB consumption, few studies have examined the predictors of SSB consumption in primary-school-aged children. The aim of this study was to understand the degree to which a child’s consumption across a range of beverages is influenced by their own attitudes and by their parents’ attitudes and parents’ consumption behaviours. Methods: A survey of 1611 Australian parent–child dyads asked children (aged 4–11) and their parents to rate a variety of drinks in terms of healthiness, taste, and cost and indicate the amount of these drinks consumed in a typical week. Zero-inflated regression analyses were conducted to identify the strength of association between children’s weekly beverage consumption, their perceptions of each beverage, their parents’ perceptions, and their parents’ weekly beverage consumption. Results: Parental consumption of a specific beverage was the strongest predictor of child consumption of that beverage, more so than the children’s perceptions of the beverage. Conclusions: These findings provide insights for developing parent and child education programmes to reduce SSB consumption. Full article

High-precision, ultra-thin angular detectable imaging upon a single pixel holds significant promise for light-field detection and reconstruction, thereby catalyzing advancements in machine vision and interaction technology. Traditional light-direction angle sensors relying on optical components like gratings and lenses face inherent constraints from diffraction limits in achieving device miniaturization. Recently, angle sensors via coupled double nanowires have demonstrated prowess in attaining high-precision angle perception of incident light at sub-wavelength device scales, which may herald a novel design paradigm for ultra-compact angle sensors. However, the current approach to measuring the three-dimensional (3D) incident light direction is unstable. In this paper, we propose a sensor concept capable of discerning the 3D light-direction based on a segmented concentric nanoring structure that is sensitive to both elevation angle (θ) and azimuth angle (ϕ) at a micrometer device scale and is validated through simulations. Through deep learning (DL) analysis and prediction, our simulations reveal that for angle scanning with a step size of 1°, the device can still achieve a detection range of 0∼360° for ϕ and 45°∼90° for θ, with an average accuracy of 0.19°, and DL can further solve some data aliasing problems to expand the sensing range. Our design broadens the angle sensing dimension based on mutual resonance coupling among nanoring segments, and through waveguide implementation or sensor array arrangements, the detection range can be flexibly adjusted to accommodate diverse application scenarios. Full article

This study explores the impact of artificial intelligence (AI) tools on the purchase intentions of members of Generation Z (Gen Z) in online shopping, using an adapted technology acceptance model (TAM). It incorporates exposure to AI, usage of AI, and knowledge about AI, alongside the existing TAM parameters of perceived usefulness of AI (PUAI) and perceived ease-of-use of AI (PEUAI). A 38-item questionnaire was distributed, yielding data from 1128 Gen Z respondents. Partial least squares structural equation modeling (PLS-SEM) and importance–performance analysis (IPA) were applied to examine the hypothesized relationships. The study identified significant direct effects of exposure, use, and knowledge on PUAI and PEUAI, and that these effects affected consumers’ purchase intentions. Indirect effects analysis revealed that PUAI and PEUAI mediate between AI exposure, use, knowledge, and purchase intentions, suggesting that greater understanding of and familiarity with AI enhance the propensity to engage in AI-powered online transactions. The ease of integrating AI into daily life and perceived AI utility enhance purchase intentions. The study offers insights for online retailers leveraging AI technologies in an effort to enhance consumer purchase experiences, emphasizing the potential of AI to positively influence choices while enhancing trust, familiarity, and the overall user experience. Full article

This study presents a novel approach to emergency vehicle classification that leverages a comprehensive set of informative audio features to distinguish between ambulance sirens, fire truck sirens, and traffic noise. A unique contribution lies in combining time domain features, including root mean square (RMS) and zero-crossing rate, to capture the temporal characteristics, like signal energy changes, with frequency domain features derived from short-time Fourier transform (STFT). These include spectral centroid, spectral bandwidth, and spectral roll-off, providing insights into the sound’s frequency content for differentiating siren patterns from traffic noise. Additionally, Mel-frequency cepstral coefficients (MFCCs) are incorporated to capture the human-like auditory perception of the spectral information. This combination captures both temporal and spectral characteristics of the audio signals, enhancing the model’s ability to discriminate between emergency vehicles and traffic noise compared to using features from a single domain. A significant contribution of this study is the integration of data augmentation techniques that replicate real-world conditions, including the Doppler effect and noise environment considerations. This study further investigates the effectiveness of different machine learning algorithms applied to the extracted features, performing a comparative analysis to determine the most effective classifier for this task. This analysis reveals that the support vector machine (SVM) achieves the highest accuracy of 99.5%, followed by random forest (RF) and k-nearest neighbors (KNNs) at 98.5%, while AdaBoost lags at 96.0% and long short-term memory (LSTM) has an accuracy of 93%. We also demonstrate the effectiveness of a stacked ensemble classifier, and utilizing these base learners achieves an accuracy of 99.5%. Furthermore, this study conducted leave-one-out cross-validation (LOOCV) to validate the results, with SVM and RF achieving accuracies of 98.5%, followed by KNN and AdaBoost, which are 97.0% and 90.5%. These findings indicate the superior performance of advanced ML techniques in emergency vehicle classification. Full article

Background: Lung cancer screening guidelines prioritize individuals with a history of smoking due to their higher risk of the disease. Methods: Our study examines the awareness and interest in low-dose computed tomography (LDCT) lung cancer screening among different smoking statuses using data from the National Cancer Institute’s Health Information National Trends Survey (HINTS) 6 (2022). We analyzed data from HINTS 6, including 3915 participants on smoking status, LDCT screening, and telehealth use. Participants were categorized as current smokers, former smokers, and non-smokers. Results: Current smokers had the highest likelihood of being recommended for LDCT screening (OR: 7.1, aOR: 10.4) compared with non-smokers. Former smokers also had increased odds of screening recommendations (OR: 3.1, aOR: 3.4) than non-smokers. Despite higher screening recommendations, current smokers exhibited significantly lower interest in cancer screening (interest rating score: 2.1) compared with non-smokers (interest rating score: 2.4) and former smokers (interest rating score: 2.5). Current smokers rated their telehealth care experiences more positively in terms of care quality compared with non-smokers. Conclusions: Our findings underscore a gap in cancer screening interest among current smokers despite their higher likelihood of being recommended for LDCT screening. The favorable perception of telehealth among current smokers provides an opportunity to enhance engagement and promote LDCT scan through telehealth care. Full article