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This study analyzes how economic, demographic, and geographic factors predict the representation of different countries in the global film festival circuit. It relies on the combination of several open-access databases, including festival programming information from the Cinando platform of the Cannes Film Market. The dataset consists of over 20,000 unique films from almost 600 festivals across the world over a decade, a total of more than 30,000 film-festival entries. It is shown that while films from large affluent countries indeed dominate the festival screen, the bias is nevertheless not fully proportional to the large demographic and economic worldwide disparities and that several smaller countries perform better than expected. Further computational simulations demonstrate how much including films from smaller countries contributes to cultural diversity, and how countries vary in cultural "trade balance" dynamics, revealing differences between net exporters and importers of festival films. This research underscores the importance of representation in film festivals and the public value of increasing cultural diversity. The data-driven insights and quantitative approaches to fe
Quantum technologies are seen as transformative, with a potential to revolutionize fields like drug discovery and machine learning. Public engagement is crucial to align these developments with societal needs and foster acceptance. This study measured the impact of an exhibit about quantum technologies at the 2024 Lowlands music festival (n = 812). Pre- and post-surveys assessed changes in attitude, concern, interest and subjective knowledge. Results showed an increase in subjective knowledge but a decrease in interest, possibly due to reduced novelty or increased perceived difficulty. These findings underscore the effectiveness of exhibits as outreach tools in informal settings and highlight the critical role of maintaining novelty and emphasizing the relevance of quantum technologies in future outreach efforts. Additionally, we emphasize the importance of assessing outreach effectiveness to ensure that objectives are successfully achieved.
This study employs a Bayesian Probit model to empirically analyze peer effects and herd behavior among consumers during the "Double 11" shopping festival, using data collected through a questionnaire survey. The results demonstrate that peer effects significantly influence consumer decision-making, with the probability of participation in the shopping event increasing notably when roommates are involved. Additionally, factors such as gender, online shopping experience, and fashion consciousness significantly impact consumers' herd behavior. This research not only enhances the understanding of online shopping behavior among college students but also provides empirical evidence for e-commerce platforms to formulate targeted marketing strategies. Finally, the study discusses the fragility of online consumption activities, the need for adjustments in corporate marketing strategies, and the importance of promoting a healthy online culture.
The ultralow frequency analogues of sound waves in Earth's magnetosphere play a crucial role in space weather, however, the public is largely unaware of this risk to our everyday lives and technology. As a way of potentially reaching new audiences, SSFX made 8 years of satellite wave recordings audible to the human ear with the aim of using it to create art. Partnering with film industry professionals, the standard processes of international film festivals were adopted by the project in order to challenge independent filmmakers to incorporate these sounds into short films in creative ways. Seven films covering a wide array of topics/genres (despite coming from the same sounds) were selected for screening at a special film festival out of 22 submissions. The works have subsequently been shown at numerous established film festivals and screenings internationally. These events have attracted diverse non-science audiences resulting in several unanticipated impacts upon them, thereby demonstrating how working with the art world can open up dialogues with both artists and audiences who would not ordinarily engage with science.
In this paper we present a study of sensing and analyzing an offline social network of participants at a large-scale music festival (8 days, 130,000+ participants). We place 33 fixed-location Bluetooth scanners in strategic spots around the festival area to discover Bluetooth-enabled mobile phones carried by the participants, and thus collect spatio-temporal traces of their mobility and interactions. We subsequently analyze the data on two levels. On the micro level, we run a community detection algorithm to reveal a variety of groups the festival participants form. On the macro level, we employ an Infinite Relational Model (IRM) in order to recover the structure of the social network related to participants' music preferences. The obtained structure in the form of clusters of concerts and participants is then interpreted using meta-information about music genres, band origins, stages, and dates of performances. We show that most of the concerts clusters can be described by one or more of the meta-features, effectively revealing preferences of participants (e.g. a cluster of US bands) and discuss the significance of the findings and the potential and limitations of the used method.
We proposed a mathematical model for designing the layout diagram of stand locations at the Macao Food Festival. The optimal layout diagram may be defined in such a way that, while requiring the distance between every pair of stands should not be too far away from each other, the crowd control is well managed so that people may patronize stands more effectively. More popular stands may have larger patronage, resulting in higher pedestrian flow nearby. Therefore, to avoid customers from packing shoulder to shoulder around more popular stands, we may treat every stand as a charged particle carrying an effective charge: the more popular a stand is, the higher the effective charge it carries. Under this assumption, the problem is then converted to the minimization problem of Coulomb electrostatic potential energy on a specific configuration of charge locations, with which the global minimum may be found by the Simulated Annealing and Metropolis Algorithm. Electrostatic energy density is interpreted as density of customers, while electric field the reversed crowd flow. Therefore, at a certain location we are able to predict the customer density by calculating the energy density and the
Human migration during the Chinese Spring Festival (SF) is the largest collective human activity of its kind in the modern era-involving about one-tenth of the world population and over six percent of the earth's land surface area. The festival results in a drop of air pollutant emissions that causes dramatic changes of atmospheric composition over China's most polluted regions. Based on satellite and in-situ measurements for the years 2005-2019 over 50 cities in eastern China, we find that the atmospheric NO2 pollution dropped by ~40% during the SF week, and fine particulate matter (PM2.5) decreased by ~30% in the following week, reflecting the effectiveness of precursor emission controls on the mitigation of secondary PM2.5 formation. However, although human activity and emissions are at the lowest level, air pollution over eastern China during the SF still far exceeds that over other worldwide pollution hotspots. Our analyses suggest that measures based solely on end-of-pipe controls and industry upgrades may not suffice to meet air quality goals. Further cleaning of the air in China depends fundamentally on sustainable advances in both heavy industry upgrades and clean energy t
Objectives Influenza outbreaks have been widely studied. However, the patterns between influenza and religious festivals remained unexplored. This study examined the patterns of influenza and Hanukkah in Israel, and that of influenza and Hajj in Bahrain, Egypt, Iraq, Jordan, Oman and Qatar. Method Influenza surveillance data of these seven countries from 2009 to 2017 were downloaded from the FluNet of the World Health Organization. Secondary data were collected for the countries' population, and the dates of Hajj and Hanukkah. We aggregated the weekly influenza A and B laboratory confirmations for each country over the study period. Weekly influenza A patterns and religious festival dates were further explored across the study period. Results We found that influenza A peaks closely followed Hanukkah in Israel in six out of seven years from 2010 to 2017. Aggregated influenza A peaks of the other six Middle East countries also occurred right after Hajj every year during the study period. Conclusions We predict that unless there is an emergence of new influenza strain, such influenza patterns are likely to persist in future years. Our results suggested that the optimal timing of mass
This research explores the dynamics of the emergency evacuation during the "Running of the Bulls" festival (Spain, 2013). As people run to escape from danger, many pedestrians stumble and fall down, while others will try to pass over them. We carefully examined three specific recordings of the running, that show this kind of behavior. We developed a microscopic model mimicking the stumbling mechanism in the context of the Social Force Model (SFM). In our model, "moving" individuals can suddenly switch to a "fallen" state when they are in the vicinity of a fallen individual. We arrived to the conclusion that the presence of a fallen pedestrian increases dramatically the falling probability of the pedestrians nearby. Also, the product between the local density gradient and the velocity of each pedestrian appears as a relevant indicator for an imminent fall. We call this the pedestrian "falling susceptibility (f_s)".
This study presents a use-case of a network of low-cost acoustic smart sensors deployed in the city of Pamplona to analyse changes in the urban soundscape during the San Fermin Festival. The sensors were installed in different areas of the city before, during, and after the event, capturing continuous acoustic data. Our analysis reveals a significant transformation in the city's sonic environment during the festive period: overall sound pressure levels increase significantly, soundscape patterns change, and the acoustic landscape becomes dominated by sounds associated with human activity. These findings highlight the potential of distributed smart acoustic monitoring systems to characterize the temporal dynamics of urban soundscapes and underscore how the large-scale event of San Fermin drastically reshapes the overall acoustic dynamics of the city of Pamplona. Additionally, to complement the objective measurements, a curated collection of real San Fermin sound recordings has been created and made publicly available, preserving the festival's unique sonic heritage.
The global landscape of art-technology institutions, including festivals, biennials, research labs, conferences, and hybrid organizations, has grown increasingly diverse, yet systematic frameworks for analyzing their multidimensional characteristics remain scarce. This paper proposes ASTRA (Art-technology Institution Spatial Taxonomy and Relational Analysis), a computational methodology combining an eight-axis conceptual framework (Curatorial Philosophy, Territorial Relation, Knowledge Production Mode, Institutional Genealogy, Temporal Orientation, Ecosystem Function, Audience Relation, and Disciplinary Positioning) with a text-embedding and clustering pipeline to map 78 cultural-technology institutions into a unified analytical space. Each institution is characterized through qualitative descriptions along the eight axes, encoded via E5-large-v2 sentence embeddings and quantized through a word-level codebook into TF-IDF feature vectors. Dimensionality reduction using UMAP, followed by agglomerative clustering (Average linkage, k=10), yields a composite score of 0.825, a silhouette coefficient of 0.803, and a Calinski-Harabasz index of 11196. Non-negative matrix factorization extra
Vision-Language Models (VLMs) often appear culturally competent but rely on superficial pattern matching rather than genuine cultural understanding. We introduce a diagnostic framework to probe VLM reasoning on fire-themed cultural imagery through both classification and explanation analysis. Testing multiple models on Western festivals, non-Western traditions, and emergency scenes reveals systematic biases: models correctly identify prominent Western festivals but struggle with underrepresented cultural events, frequently offering vague labels or dangerously misclassifying emergencies as celebrations. These failures expose the risks of symbolic shortcuts and highlight the need for cultural evaluation beyond accuracy metrics to ensure interpretable and fair multimodal systems.
Mathematics is often perceived as difficult or inaccessible, yet meaningful engagement can arise in unexpected places. In this article we describe a multi-year exploration of mathematical outreach through games, puzzles, exhibitions, and artistic activities. Starting from a small science festival exhibit, our work developed into a broad collection of experiences showcased at game festivals, museums, and the World Expos in Dubai (2021/2022) and Osaka (2025). We discuss the principles that shaped these activities -- simplicity, atmosphere, mediation, and progressive depth -- and how mathematical ideas from topology, geometry, and logic can be incorporated into playful and creative formats. The story illustrates how low-threshold engagement and carefully designed experiences can open doors to research-level mathematics for audiences of all ages and backgrounds.
As people engage with the social media landscape, popular platforms rise and fall. As current research uncovers the experiences people have on various platforms, rarely do we engage with the sociotechnical migration processes when joining and leaving them. In this paper, we asked 32 visitors of a science communication festival to draw out artifacts that we call Social Media Journey Maps about the social media platforms they frequented, and why. By combining qualitative content analysis with a graph representation of Social Media Journeys, we present how social media migration processes are motivated by the interplay of environmental and platform factors. We find that peer-driven popularity, the timing of feature adoption, and personal perceptions of migration causes - such as security - shape individuals' reasoning for migrating between social media platforms. With this work, we aim to pave the way for future social media platforms that foster meaningful and enriching online experiences for users.
This paper presents Negative Shanshui, a real-time interactive AI synthesis approach that reinterprets classical Chinese landscape ink painting, i.e., shanshui, to engage with ecological crises in the Anthropocene. Negative Shanshui optimizes a fine-tuned Stable Diffusion model for real-time inferences and integrates it with gaze-driven inpainting, frame interpolation; it enables dynamic morphing animations in response to the viewer's gaze and presents as an interactive virtual reality (VR) experience. The paper describes the complete technical pipeline, covering the system framework, optimization strategies, gaze-based interaction, and multimodal deployment in an art festival. Further analysis of audience feedback collected during its public exhibition highlights how participants variously engaged with the work through empathy, ambivalence, and critical reflection.
Infrared thermography has gained interest as a tool for non-contact measurement of blood circulation and skin blood flow due to cardiac activity. Partiularly, blood vessels on the surface, such as on the back of the hand, are suited for visualization. However, standardized methodologies have not yet been established for areas such as the face and neck, where many blood vessels are lie deeper beneath the surface, and external stimulation for measurement could be harmful. Here we propose Synchro-Thermography for stable monitoring of facial temperature changes associated with heart rate variability. We conducted experiments with eight subjects and measured minute temperature changes with an amplitude of about \SI{10}{mK} on the forehead and chin. The proposed method improves the temperature resolution by a factor of 2 or more, and can stably measure skin temperature changes caused by blood flow. This skin temperature change could be applied to physiological sensing such as blood flow changes due to injury or disease, or as an indicator of stress.
Large Language Models (LLMs) show potential for enhancing robotic path planning. This paper assesses visual input's utility for multimodal LLMs in such tasks via a comprehensive benchmark. We evaluated 15 multimodal LLMs on generating valid and optimal paths in 2D grid environments, simulating simplified robotic planning, comparing text-only versus text-plus-visual inputs across varying model sizes and grid complexities. Our results indicate moderate success rates on simpler small grids, where visual input or few-shot text prompting offered some benefits. However, performance significantly degraded on larger grids, highlighting a scalability challenge. While larger models generally achieved higher average success, the visual modality was not universally dominant over well-structured text for these multimodal systems, and successful paths on simpler grids were generally of high quality. These results indicate current limitations in robust spatial reasoning, constraint adherence, and scalable multimodal integration, identifying areas for future LLM development in robotic path planning.
The preservation of cultural heritage, as mandated by the United Nations Sustainable Development Goals (SDGs), is integral to sustainable urban development. This paper focuses on the Dragon Boat Festival, a prominent event in Chinese cultural heritage, and proposes leveraging Virtual Reality (VR), to enhance its preservation and accessibility. Traditionally, participation in the festival's dragon boat races was limited to elite athletes, excluding broader demographics. Our proposed solution, named MetaDragonBoat, enables virtual participation in dragon boat racing, offering immersive experiences that replicate physical exertion through a cultural journey. Thus, we build a digital twin of a university campus located in a region with a rich dragon boat racing tradition. Coupled with three paddling techniques that are enabled by either commercial controllers or physical paddle controllers with haptic feedback, diversified users can engage in realistic rowing experiences. Our results demonstrate that by integrating resistance into the paddle controls, users could simulate the physical effort of dragon boat racing, promoting a deeper understanding and appreciation of this cultural herit
Large Language Models (LLMs) have demonstrated significant capabilities in understanding and generating human language, contributing to more natural interactions with complex systems. However, they face challenges such as ambiguity in user requests processed by LLMs. To address these challenges, this paper introduces and evaluates a multi-agent debate framework designed to enhance detection and resolution capabilities beyond single models. The framework consists of three LLM architectures (Llama3-8B, Gemma2-9B, and Mistral-7B variants) and a dataset with diverse ambiguities. The debate framework markedly enhanced the performance of Llama3-8B and Mistral-7B variants over their individual baselines, with Mistral-7B-led debates achieving a notable 76.7% success rate and proving particularly effective for complex ambiguities and efficient consensus. While acknowledging varying model responses to collaborative strategies, these findings underscore the debate framework's value as a targeted method for augmenting LLM capabilities. This work offers important insights for developing more robust and adaptive language understanding systems by showing how structured debates can lead to improve
We present one of the first comprehensive field datasets capturing dense pedestrian dynamics across multiple scales, ranging from macroscopic crowd flows over distances of several hundred meters to microscopic individual trajectories, including approximately 7,000 recorded trajectories. The dataset also includes a sample of GPS traces, statistics on contact and push interactions, as well as a catalog of non-standard crowd phenomena observed in video recordings. Data were collected during the 2022 Festival of Lights in Lyon, France, within the framework of the French-German MADRAS project, covering pedestrian densities up to 4 individuals per square meter.