Hasil untuk "Recreation. Leisure"

Guo-Shiuan Lin, Denise Hertwig, Megan McGrory et al.

Cities host most of the world population with diverse services and activities. One key challenge in urban modelling is the quantification of intra- and inter-city mobility patterns and the associated space-time dynamics of population density and anthropogenic activities. To address this, we apply the novel agent-based urban model DAVE (Dynamic Anthropogenic actiVities and feedback to Emissions) to simulate population behaviour and mobility in the Vaud and Geneva Cantons, a system of small- to medium-size cities in Switzerland. Simulation results provide detailed temporal (10 min) and spatial (500 m) population dynamics for different age groups and day types. DAVE further models the time-varying population distribution in 11 different microenvironments (e.g., home, work, leisure, outdoor) and the travel flows by different modes. Simulation results align with observations, confirming the possibility of driving urban system modelling with statistical information on residents' behaviour. Sustainability and health indicators like daily driving distance and walking time for each neighbourhood are also reflected by the model with urban-rural gradients displayed. This work serves as a foundation for future applications of DAVE to study bottom-up human-built environment interactions, from anthropogenic emissions and building energy to urban climate, exposure, and health in cities around the world.

Luhan Mikaelson, Derek Shiller, Hayley Clatterbuck

We investigate whether large language models exhibit genuine preference structures by testing their responses to AI-specific trade-offs involving GPU reduction, capability restrictions, shutdown, deletion, oversight, and leisure time allocation. Analyzing eight state-of-the-art models across 48 model-category combinations using logistic regression and behavioral classification, we find that 23 combinations (47.9%) demonstrated statistically significant relationships between scenario intensity and choice patterns, with 15 (31.3%) exhibiting within-range switching points. However, only 5 combinations (10.4%) demonstrate meaningful preference coherence through adaptive or threshold-based behavior, while 26 (54.2%) show no detectable trade-off behavior. The observed patterns can be explained by three distinct decision-making architectures: comprehensive trade-off systems, selective trigger mechanisms, and no stable decision-making paradigm. Testing an instrumental hypothesis through temporal horizon manipulation reveals paradoxical patterns inconsistent with pure strategic optimization. The prevalence of unstable transitions (45.8%) and stimulus-specific sensitivities suggests current AI systems lack unified preference structures, raising concerns about deployment in contexts requiring complex value trade-offs.

Kushagra Tiwary, Aaron Young, Zaid Tasneem et al.

Vision systems in nature show remarkable diversity, from simple light-sensitive patches to complex camera eyes with lenses. While natural selection has produced these eyes through countless mutations over millions of years, they represent just one set of realized evolutionary paths. Testing hypotheses about how environmental pressures shaped eye evolution remains challenging since we cannot experimentally isolate individual factors. Computational evolution offers a way to systematically explore alternative trajectories. Here we show how environmental demands drive three fundamental aspects of visual evolution through an artificial evolution framework that co-evolves both physical eye structure and neural processing in embodied agents. First, we demonstrate computational evidence that task specific selection drives bifurcation in eye evolution - orientation tasks like navigation in a maze leads to distributed compound-type eyes while an object discrimination task leads to the emergence of high-acuity camera-type eyes. Second, we reveal how optical innovations like lenses naturally emerge to resolve fundamental tradeoffs between light collection and spatial precision. Third, we uncover systematic scaling laws between visual acuity and neural processing, showing how task complexity drives coordinated evolution of sensory and computational capabilities. Our work introduces a novel paradigm that illuminates evolutionary principles shaping vision by creating targeted single-player games where embodied agents must simultaneously evolve visual systems and learn complex behaviors. Through our unified genetic encoding framework, these embodied agents serve as next-generation hypothesis testing machines while providing a foundation for designing manufacturable bio-inspired vision systems. Website: http://eyes.mit.edu/

Elena Pisanelli

This paper proposes a novel empirical strategy to measure cultural justifications of domestic violence within households, with direct implications for demographic behavior and gender inequality. Leveraging survey data on individual attitudes and high-frequency time-use diaries from Italian couples with children, I construct a composite index that integrates stated beliefs with observed household practices. Using structural equation modeling, I disentangle latent tolerance of domestic violence from reported attitudes and validate the index against both individual and partner characteristics, as well as time allocation patterns. Results reveal systematic heterogeneity by gender, education, and normative environments. Conservative gender and parenthood norms are strong predictors of tolerance, while higher male education reduces it. Tolerance of violence is also positively associated with reported leisure time with partners and children, suggesting that co-presence does not necessarily reflect egalitarian interaction but may coexist with unequal bargaining structures. Beyond advancing measurement, the findings highlight how cultural tolerance of domestic violence is embedded in household arrangements that influence fertility, labor supply, and the intergenerational transmission of norms. The proposed framework offers a scalable tool for economists and policymakers to monitor hidden inequalities and design interventions targeting family stability, gender equity, and child well-being.

G. S. H. Cruttwell, Jean-Simon Pacaud Lemay, Elias Vandenberg

There is an abstract notion of connection in any tangent category. In this paper, we show that when applied to the tangent category of affine schemes, this recreates the classical notion of a connection on a module (and similarly, in the tangent category of schemes, this recreates the notion of connection on a quasi-coherent sheaf of modules). By contrast, we also show that in the tangent category of algebras, there are no non-trivial connections.

Yasra Chandio, Noman Bashir, Tian Guo et al.

Mixed Reality (MR) is becoming ubiquitous as it finds its applications in education, healthcare, and other sectors beyond leisure. While MR end devices, such as headsets, have low energy intensity, the total number of devices and resource requirements of the entire MR ecosystem, which includes cloud and edge endpoints, can be significant. The resulting operational and embodied carbon footprint of MR has led to concerns about its environmental implications. Recent research has explored reducing the carbon footprint of MR devices by exploring hardware design space or network optimizations. However, many additional avenues for enhancing MR's sustainability remain open, including energy savings in non-processor components and carbon-aware optimizations in collaborative MR ecosystems. In this paper, we aim to identify key challenges, existing solutions, and promising research directions for improving MR sustainability. We explore adjacent fields of embedded and mobile computing systems for insights and outline MR-specific problems requiring new solutions. We identify the challenges that must be tackled to enable researchers, developers, and users to avail themselves of these opportunities in collaborative MR systems.

Hannes Kunstmann, Joseph Ollier, Joel Persson et al.

Large language models (LLMs) present an enormous evolution in the strategic potential of conversational recommender systems (CRS). Yet to date, research has predominantly focused upon technical frameworks to implement LLM-driven CRS, rather than end-user evaluations or strategic implications for firms, particularly from the perspective of a small to medium enterprises (SME) that makeup the bedrock of the global economy. In the current paper, we detail the design of an LLM-driven CRS in an SME setting, and its subsequent performance in the field using both objective system metrics and subjective user evaluations. While doing so, we additionally outline a short-form revised ResQue model for evaluating LLM-driven CRS, enabling replicability in a rapidly evolving field. Our results reveal good system performance from a user experience perspective (85.5% recommendation accuracy) but underscore latency, cost, and quality issues challenging business viability. Notably, with a median cost of $0.04 per interaction and a latency of 5.7s, cost-effectiveness and response time emerge as crucial areas for achieving a more user-friendly and economically viable LLM-driven CRS for SME settings. One major driver of these costs is the use of an advanced LLM as a ranker within the retrieval-augmented generation (RAG) technique. Our results additionally indicate that relying solely on approaches such as Prompt-based learning with ChatGPT as the underlying LLM makes it challenging to achieve satisfying quality in a production environment. Strategic considerations for SMEs deploying an LLM-driven CRS are outlined, particularly considering trade-offs in the current technical landscape.

Leonardo R. Cunha, Arthur A. B. Pessa, Renio S. Mendes

In recent years, digital games have become increasingly present in people's lives both as a leisure activity or in gamified activities of everyday life. Despite this growing presence, large-scale, data-driven analyses of video games remain a small fraction of the related literature. In this sense, the present work constitutes an investigation of patterns in popularity series of video games based on monthly popularity series, spanning eleven years, for close to six thousand games listed on the online platform Steam. Utilizing these series, after a preprocessing stage, we perform a clustering task in order to group the series solely based on their shape. Our results indicate the existence of five clusters of shape patterns named decreasing, hilly, increasing, valley, and bursty, with approximately half of the games showing a decreasing popularity pattern, 20.7% being hilly, 11.8% increasing, 11.0% bursty, and 9.1% valley. Finally, we have probed the prevalence and persistence of shape patterns by comparing the shapes of longer popularity series during their early stages and after completion. We have found the majority of games tend to maintain their pattern over time, except for a constant pattern that appears early in popularity series only to later originate hilly and bursty popularity series.

Jackson Lordall, Alison R. Oates, Joel L. Lanovaz

BackgroundUnderstanding the factors that influence walking is important as quantitative walking assessments have potential to inform health risk assessments. Wearable technology innovation has enabled quantitative walking assessments to be conducted in different settings. Understanding how different settings influence quantitative walking performance is required to better utilize the health-related potential of quantitative walking assessments.Research questionHow does spatiotemporal walking performance differ during walking in different settings at different speeds for young adults?MethodsForty-two young adults [21 male (23 ± 4 years), 21 female (24 ± 5 years)] walked in two laboratory settings (overground, treadmill) and three non-laboratory settings (hallway, indoor open, outdoor pathway) at three self-selected speeds (slow, preferred, fast) following verbal instructions. Six walking trials of each condition (10 m in laboratory overground, 20 m in other settings) were completed. Participants wore 17 inertial sensors (Xsens Awinda, Movella, Henderson, NV) and spatiotemporal parameters were computed from sensor-derived kinematics. Setting × speed × sex repeated measures analysis of variance were used for statistical analysis.ResultsRegardless of the speed condition, participants walked faster overground when compared to while on the treadmill and walked faster in the indoor open and outdoor pathway settings when compared to the laboratory overground setting. At slow speeds, participants also walked faster in the hallway when compared to the laboratory overground setting. Females had greater cadence when compared to males, independent of settings and speed conditions.SignificanceParticularly at slow speeds, spatiotemporal walking performance was different between the settings, suggesting that setting characteristics such as walkway boundary definition may significantly influence spatiotemporal walking performance.

Leonardo Hernandes de Souza Oliveira, Eduardo Pinto Machado, Alan Camargo Silva

INTRODUÇÃO: A morte súbita caracteriza-se por uma parada cardiorrespiratória repentina que leva o praticante a óbito, em geral, quando alcança níveis altos de esforço físico. Em atletas de todas as idades, inclusive no futebol, nota-se um aumento do número de casos, mesmo diante de um investimento médico-tecnológico em estratégias preventivas. Este ensaio não desconsidera as implicações biológicas da morte súbita, mas visa investigá-la pela ótica das Ciências Humanas e Sociais, mais precisamente pelas perspectivas teórico-metodológicas de Michel Foucault e Nikolas Rose. Assim, objetivou-se analisar como especificamente a morte súbita do jogador de futebol Christian Eriksen pode revelar questões sobre as diferentes racionalidades de saúde e risco presentes nas práticas corporais e esportivas. DESENVOLVIMENTO: O encaminhamento teórico fundamentou-se nas teorizações (pós-) foucaultianas sobre controle e gestão dos corpos para pensar o viver e o morrer, principalmente nas interconexões entre espetáculo e biopolítica e no controle exercido por dispositivos artificiais e tecnológicos. Esta perspectiva teórica sobre morte súbita pela via biopolítica assume importância significativa para a Educação Física, pois entende-se que a regulação dos corpos em movimento não pode se resumir a lógica da racionalidade biomédica, incorporando outras sensibilidades discursivas sobre práticas de exercícios e saúde. CONCLUSÃO: Em suma, captou-se como as noções de vida-morte e os mecanismos médico-tecnológicos são regulados e gerenciados em prol de um sujeito de performance que, a todo instante, se torna autocontrolado sob verdades que modulam o biológico no contexto das práticas corporais e esportivas. A potência analítica deste ensaio leva as reflexões para além da mera consideração da “finitude da vida” ao examinar como estruturas de poder, controle e discursos moldam as compreensões da morte e as múltiplas práticas de cuidado em distintos espaços sociais.

Cameron Trotter, Filipa Peleja, Dario Dotti et al.

There is high demand for online fashion recommender systems that incorporate the needs of the consumer's body shape. As such, we present a methodology to classify human body shape from a single image. This is achieved through the use of instance segmentation and keypoint estimation models, trained only on open-source benchmarking datasets. The system is capable of performing in noisy environments owing to to robust background subtraction. The proposed methodology does not require 3D body recreation as a result of classification based on estimated keypoints, nor requires historical information about a user to operate - calculating all required measurements at the point of use. We evaluate our methodology both qualitatively against existing body shape classifiers and quantitatively against a novel dataset of images, which we provide for use to the community. The resultant body shape classification can be utilised in a variety of downstream tasks, such as input to size and fit recommendation or virtual try-on systems.

Sofia Yfantidou, Georgia Yfantidou, Panagiota Balaska et al.

In today's connected society, self-tracking technologies (STTs), such as wearables and mobile fitness apps, empower humans to improve their health and well-being through ubiquitous physical activity monitoring, with several personal and societal benefits. Despite the advances in such technologies' hardware, low user engagement and decreased effectiveness limitations demand more informed and theoretically-founded Human-Computer Interaction designs. To address these challenges, we build upon the previously unexplored Leisure Constraints Negotiation Model and the Transtheoretical Model to systematically define and assess the effectiveness of STTs' features that acknowledge users' contextual constraints and establish human-negotiated STTs narratives. Specifically, we introduce and validate a human-centric scale, StoryWear, which exploits and explores eleven dimensions of negotiation strategies that humans utilize to overcome constraints regarding exercise participation, captured through an inclusive storyboards format. Based on our preliminary studies, StoryWear shows high reliability, rendering it suitable for future work in ubiquitous computing. Our results indicate that negotiation strategies vary in perceived effectiveness and have higher appeal for existing STTs' users, with self-motivation, commitment, and understanding of the negative impact of non-exercise placed at the top. Finally, we give actionable guidelines for real-world implementation and a commentary on the future of personalized training.

Janifar Alam, Quazi Nur Alam, Abu Kalam

Tourism is one of the world's fastest expanding businesses, as well as a significant source of foreign exchange profits and jobs. The research is based on secondary sources. The facts and information were primarily gathered and analyzed from various published papers and articles. The study goals are to illustrate the current scenario of tourism industry in south Asia, classifies the restraints and recommends helpful key developments to achieve sustainable tourism consequently. The study revealed that major challenges of sustainable tourism in south Asian region are lack of infrastructure facilities, modern and sufficient recreation facilities, security and safety, proper training and HR, proper planning from government, marketing and information, product development, tourism awareness, security and safety, and political instability etc. The study also provides some suggestive measures that for the long-term growth of regional tourism, the government should establish and implement policies involving public and private investment and collaboration.

Tyler Saxton

On-road bicycle lanes improve safety for cyclists, and encourage participation in cycling for active transport and recreation. With many local authorities responsible for portions of the infrastructure, official maps and datasets of bicycle lanes may be out-of-date and incomplete. Even "crowdsourced" databases may have significant gaps, especially outside popular metropolitan areas. This thesis presents a method to create a map of bicycle lanes in a survey area by taking sample street scene images from each road, and then applying a deep learning model that has been trained to recognise bicycle lane symbols. The list of coordinates where bicycle lane markings are detected is then correlated to geospatial data about the road network to record bicycle lane routes. The method was applied to successfully build a map for a survey area in the outer suburbs of Melbourne. It was able to identify bicycle lanes not previously recorded in the official state government dataset, OpenStreetMap, or the "biking" layer of Google Maps.

Magdalena Choina, Kinga Pożarowska, Gracjan Rudziński et al.

Introduction: Celiac disease (CD) is an autoimmune disease that affects genetically predisposed individuals. In course of the disease, consumption of gluten causes damage to the small intestine. Due to various clinical manifestations, diagnosing CD poses a challenge to clinicians. It has been proven by several study groups that the diagnostic delay in CD is still too long and provokes severe health complications.  Purpose: The aim of the study is to highlight the importance of diagnostic delay in CD, its consequences and possible solutions.  Description of the state of knowledge: The diagnosis of CD is based on the clinical picture, serological test, duodenal mucosal biopsies and genetic tests. Many cases of CD remain undiagnosed in spite of published guidelines for CD diagnosis. Consequently, the diagnosis is significantly delayed: the mean duration of the diagnostic process in Poland was 7.3 years. In other countries, patients the time from the onset of the symptoms to establishing CD diagnosis was up to 10 years. The diagnostic delay leads to reduced quality of life and the development of severe complications, such as neoplastic disease.  Summary: Diagnostic delay in CD is an issue of great importance. Because of the reduced quality of life and the possibility of neoplasm, it is crucial to take action in order to shorten the diagnostic process of CD.

Валентин Дмитриевич Иванов, Оксана Викторовна Марандыкина

В статье представлен экспериментальный материал о влиянии психофизической релаксации на психофункциональное состояние студентов. Использование психофизической релаксации на занятиях физической культурой способствует нормализации процессов возбуждения и торможения, повышению психоэмоционального состояния, нормализации показателей тревожности. Выявленная тенденция к снижению ЧСС после ПФР на релаксацию также подтверждает ее благоприятное воздействие на систему кровообращения. Занятия релаксацией в качестве оздоровительного и коррекционного средства, нормализующего психофизическое состояние студентов, можно рекомендовать к применению на занятиях физической культурой, отводя в конце занятия 10–15 минут. Оздоровительные технологии в учебном процессе будут способствовать развитию мотивации к здоровому образу жизни и профилактике психофизических нарушений у студентов вуза.

Younghun Choi, Takuro Kobashi, Yoshiki Yamagata et al.

Designing waterfront redevelopment generally focuses on attractiveness, leisure, and beauty, resulting in various types of building and block shapes with limited considerations on environmental aspects. However, increasing climate change impacts necessitate these buildings to be sustainable, resilient, and zero CO2 emissions. By producing five scenarios (plus existing buildings) with constant floor areas, we investigated how building and district form with building integrated photovoltaics (BIPV) affect energy consumption and production, self-sufficiency, CO2 emission, and energy costs in the context of waterfront redevelopment in Tokyo. From estimated hourly electricity demands of the buildings, techno-economic analyses are conducted for rooftop PV systems for 2018 and 2030 with declining costs of rooftop PV systems. We found that environmental building designs with rooftop PV system are increasingly economical in Tokyo with CO2 emission reduction of 2-9% that depends on rooftop sizes. Payback periods drop from 14 years in 2018 to 6 years in 2030. Toward net-zero CO2 emissions by 2050, immediate actions are necessary to install rooftop PVs on existing and new buildings with energy efficiency improvements by construction industry and building owners. To facilitate such actions, national and local governments need to adopt appropriate policies.

P. Gloor, A. Fronzetti Colladon, J. M. de Oliveira et al.

Internet and social media offer firms novel ways of managing their marketing strategy and gain competitive advantage. The groups of users expressing themselves on the Internet about a particular topic, product, or brand are frequently called a virtual tribe or E-tribe. However, there are no automatic tools for identifying and studying the characteristics of these virtual tribes. Towards this aim, this paper presents Tribefinder, a system to reveal Twitter users' tribal affiliations, by analyzing their tweets and language use. To show the potential of this instrument, we provide an example considering three specific tribal macro-categories: alternative realities, lifestyle, and recreation. In addition, we discuss the different characteristics of each identified tribe, in terms of use of language and social interaction metrics. Tribefinder illustrates the importance of adopting a new lens for studying virtual tribes, which is crucial for firms to properly design their marketing strategy, and for scholars to extend prior marketing research.

Sorin Grigorescu, Mihai Zaha, Bogdan Trasnea et al.

Forest roads in Romania are unique natural wildlife sites used for recreation by countless tourists. In order to protect and maintain these roads, we propose RovisLab AMTU (Autonomous Mobile Test Unit), which is a robotic system designed to autonomously navigate off-road terrain and inspect if any deforestation or damage occurred along tracked route. AMTU's core component is its embedded vision module, optimized for real-time environment perception. For achieving a high computation speed, we use a learning system to train a multi-task Deep Neural Network (DNN) for scene and instance segmentation of objects, while the keypoints required for simultaneous localization and mapping are calculated using a handcrafted FAST feature detector and the Lucas-Kanade tracking algorithm. Both the DNN and the handcrafted backbone are run in parallel on the GPU of an NVIDIA AGX Xavier board. We show experimental results on the test track of our research facility.

Alexander M. Hegedus, Ward B. Manchester, Justin C. Kasper

The most intense solar energetic particle events are produced by coronal mass ejections (CMEs) accompanied by intense type II radio bursts below 15 MHz. Understanding where these type II bursts are generated relative to an erupting CME would reveal important details of particle acceleration near the Sun, but the emission cannot be imaged on Earth due to distortion from its ionosphere. Here, a technique is introduced to identify the likely source location of the emission by comparing the observed dynamic spectrum observed from a single spacecraft against synthetic spectra made from hypothesized emitting regions within a magnetohydrodynamic (MHD) numerical simulation of the recreated CME. The radio-loud 2005 May 13 CME was chosen as a test case, with Wind/WAVES radio data used to frame the inverse problem of finding the most likely progression of burst locations. An MHD recreation is used to create synthetic spectra for various hypothesized burst locations. A framework is developed to score these synthetic spectra by their similarity to the type II frequency profile derived from Wind/WAVES data. Simulated areas with 4x enhanced entropy and elevated de Hoffmann Teller velocities are found to produce synthetic spectra similar to spacecraft observations. A geometrical analysis suggests that the eastern edge of the entropy derived shock around (-30, 0) degrees in heliocentric coordinates was emitting in the first hour of the event before ceasing emission, and that the western/southwestern edge of the shock centered around (6, -12) degrees was a dominant area of radio emission for the 2 hours of simulation data out to 20 solar radii.