Non-pharmaceutical interventions (NPIs) are crucial for controlling pandemics, but existing research often overlooks the heterogeneity of individual behavior, which can lead to inaccurate evaluations of the effectiveness of strategies. In this paper, we use a large dataset of fine-grained real-world individual trajectory data from a major Chinese city to examine the trade-off between the epidemic containment effectiveness and economic cost of different NPIs. Our findings reveal significant variations in the outcomes of different NPIs across activation mechanisms and initial scales of undetected transmission. Based on these results, we construct a two-dimensional evaluation framework that comprehensively evaluates the impact of both the containment effectiveness and economic cost, which suggests that implementing stringent strategies-such as lockdown or contact tracing-at low activation thresholds can achieve optimal epidemic control with minimal economic cost. Our study provides a data-driven decision-making framework for understanding the implementation effectiveness and applicability of emergency management policies within urban systems.
The `15-minute city' has emerged as a central paradigm in urban planning, promoting universal access to work and essential services within short travel times. Its feasibility-particularly for commuting to work-has however rarely been examined quantitatively. Here, we show that proximity to employment is fundamentally constrained by the internal structure of urban economies. Combining urban geometry with empirically observed firm-size distributions, we derive a lower bound on commuting times that holds independently of planning choices or transport technologies. This bound reveals a sharp transition: when employment is sufficiently concentrated, no spatial rearrangement of workplaces can ensure uniformly short commutes, even under optimal placement. Applied to Paris and its near suburbs, we find that achieving universal 15-minute commutes would require substantial economic restructuring or differentiated mobility strategies. The relevant question is therefore not whether an $x$-minute city is achievable, but what the minimal feasible $x$ is given a city's economic structure and spatial scale.
The hierarchy and proximity are key dimensions of urban relational processes, but their interplay in shaping intercity interactions and the underlying structures of city systems remain unclear. We develop a novel geometric model of city systems embedding intercity mobility into a latent hyperbolic geometry, which unravels the measures of hierarchy and proximity accounting for their interplay. It is successfully validated against 12 different nationwide intercity mobility datasets. We find a bottom-up emergence of city hierarchies, along which the variations of city-hinterland relations are non-stationary in terms of their nesting and range properties. Such non-stationarity originates from trade-offs between city hierarchy and hinterland range in determining the formation of city-hinterland structures. Hierarchy- and proximity-dominated urban processes can be elucidated from examining dynamics of the trade-offs. The revealed urban relational processes of city systems are at the core of the emerging science of cities and crucial for spatial planning and regional policymaking.
Abstract In animals where males engage in multiple matings, sperm depletion can substantially reduce the reproductive success of both sexes. However, little is known about how successive matings affect sperm depletion, fertilization rates and mating behaviour. Here, we investigated this phenomenon under laboratory conditions. Medaka (Oryzias latipes), an externally fertilizing fish, is an ideal model to test predictions of sperm depletion because there are established methods to observe its mating and count sperm. Medaka males mated with multiple females (19 per day, on average; range, 4–27), experiencing significant sperm depletion, with sperm release declining markedly after the first few matings, reaching only 0.5–6.3% by the last mating of the day. Fertilization rates decreased, particularly after approximately 10 consecutive matings, although there was some recovery in the next-day’s matings. The decline in courtship effort and mating duration probably resulted from the males becoming increasingly fatigued. Despite the reduced sperm availability, females did not adjust their clutch size as a counterstrategy. These results suggest substantial reproductive costs for males and the potential for sexual conflict owing to limited sperm availability. For species with frequent successive mating, these findings highlight the need to reconsider reproductive strategies and their impact on sexual selection.
Desde la mirada de la antropología del turismo, el presente artículo demostrará como el auge del modelo de turismo de masa de sol y playa en la isla de Mallorca opacó las potencialidades iniciadas del turismo más elitista entorno a la ciudad de Palma. En primer lugar, recordaremos los inicios del turismo en Mallorca que surgieron entorno a la puesta en valor de Palma. En segundo lugar, nos centraremos en la conversión ulterior de Palma como destino secundario como consecuencia paradójicamente del éxito del turismo de sol y playa en Mallorca. Finalmente, en tercer lugar, analizaremos la recuperación reciente del turismo urbano en Palma, a partir de la valorización de las nuevas lógicas de diversificación del turismo.
Recreation leadership. Administration of recreation services, The city as an economic factor. City promotion
Yoko Eurídice Flores Juárez, Sonia Gayosso, Aide Maricel Carrizal Alonso
This research explores the delicate balance between preserving traditional artisanal techniques and embracing innovation in Huejutla de Reyes, Hidalgo, Mexico. Through a pilot study involving 30 artisans, we identified significant barriers to technological adoption while recognizing opportunities for sustainable development. The findings reveal that 95% of artisans maintain traditional techniques, yet only 20% utilize digital tools for promotion and sales. Based on these insights, we developed the Integrated Model of Innovation and Artisanal Preservation (MIIPA), which addresses four strategic dimensions: tradition, innovation, sustainable development, and smart marketing. The model provides a structured framework that respects cultural identity while encouraging gradual modernization. By incorporating principles of regenerative tourism and the creative economy, MIIPA offers practical strategies for strengthening the artisanal sector's resilience and economic viability without compromising its cultural authenticity. This approach represents a significant contribution to the preservation of artisanal heritage in the context of an increasingly globalized marketplace
Recreation leadership. Administration of recreation services, The city as an economic factor. City promotion
Abstract The digital economy (DE), as a new form of economic element in building a new pattern of economic development, is an important driving factor for promoting the industrial green transformation (IGT). Based on panel data from 31 resource-based cities in the Yangtze River Economic Belt (YREB) from 2013 to 2022, this article uses a two-way fixed-effects model, intermediary effects model, and threshold effects model to study the impact of the DE in resource-based cities along the YREB on IGT. The research findings are as follows: The DE significantly promotes IGT and drives it through the enhancement of technological innovation; The promotion effect of the DE on IGT has a non-linear relationship, indicating the presence of threshold effects; Group regression analysis shows that there is heterogeneity in the impact of the DE on IGT concerning city development level, time, and city type. The above findings provide new insights and empirical evidence for understanding issues related to the DE and green economy.
A smart city is essential for sustainable urban development. In addition to citizen engagement, a smart city enables connected infrastructure, data-driven decision making and smart mobility. For most of these features, network data plays a critical role, particularly from public Wi-Fi infrastructures, where cities can benefit from optimized services such as public transport management and the safety and efficiency of large events. One of the biggest concerns in developing a smart city is using secure and private data. This is particularly relevant in the case of Wi-Fi network data, where sensitive information can be collected. This paper specifically addresses the problem of sharing secure data to enhance the quality of the Wi-Fi network in a city. Despite the high importance of this type of data, related work focuses on improving the safety of mobility patterns, targeting only the protection of MAC addresses. On the opposite side, we provide a practical methodology for safeguarding all attributes in real Wi-Fi network data. This study was developed in collaboration with a multidisciplinary team of legal experts, data custodians and technical privacy specialists, resulting in high-quality data. On top of that, we show how to integrate the legal considerations for secure data sharing. Our approach promotes data-driven innovation and privacy awareness in the context of smart city initiatives, which have been tested in a real scenario.
Many developed countries need to plan urban policies based on multidimensional factors related to population change. However, empirical research has been inconsistent with respect to identifying these factors, including economic-, social-, and urban-planning-related factors. The purpose of this study is to clarify the nonlinear multidimensional factors that are correlated with population changes according to the city size. In the analysis, the population change rate was defined as the outcome variable, and 269 economic, social, and educational index (ESE index) were used as predictor variables. Data were stratified according to three city sizes. Using the ESE index, the XGBoost algorithm was used to analyze the nonlinear relationship between the population change rate and multidimensional data. As a key result, population changes were strongly correlated with social-related indicators, such as the population change rate among persons ages 0–14 years in small-sized cities, the natural population change rate in medium-sized cities, and the migration change rate in large-sized cities. Regarding the population decline, Japan has 1304 shrinking cities, which are primarily comprised of medium-sized and small-sized cities. In such cities, other than social-related factors, population changes correlated with the financial strength index as an economic-related factor in medium-sized cities and the designation of underpopulated areas as an urban-planning-related factor in small-sized cities. Among the multidimensional factors, cities of different sizes were characterized by factors other than social-related indicators. These multifaceted factors could provide preliminary insights for urban policymakers to explore various policy measures on which they need to focus, depending on the city’s size.
This study investigates city dynamics employing a nonextensive diffusion equation suited for addressing diffusion within a fractal medium, where the nonadditive parameter, $q$, plays a relevant role. The findings demonstrate the efficacy of this approach in determining the relation between the fractal dimension of the city, the allometric exponent and $q$, and elucidating the stationary phase of urban evolution. The dynamic methodology facilitates the correlation of the fractal dimension with both the entropic index and the urban scaling exponent identified in data analyses. The results reveal that the scaling behaviour observed in cities aligns with the fractal dimension measured through independent methods. Moreover, the interpretation of these findings underscores the intimate connection between the fractal dimension and social interactions within the urban context. This research contributes to a deeper comprehension of the intricate interplay between human behaviour, urban dynamics, and the underlying fractal nature of cities.
Óscar Gutiérrez-Aragón, Ariadna Gassiot-Melian, Meritxell López-Corbillón
et al.
El turismo es un fenómeno en constante crecimiento desde hace décadas a nivel global. Taiwán, uno de los países asiáticos con mayor crecimiento económico, ha incrementado notablemente el número de turistas en el presente siglo. En este contexto, conocer las motivaciones de los turistas es una variable fundamental para la toma de decisiones en este sector, uno de los más susceptibles a verse afectado por una gran diversidad de factores. El objetivo principal de este estudio es el análisis en profundidad de las motivaciones que inducen a viajar a los millennials y centennials de Taiwán. tratando de determinar y comprender el perfil turístico de los jóvenes taiwaneses confrontándolo desde un enfoque occidental. Para ello se ha utilizado metodología de tipo cuantitativo, mediante estadística descriptiva e inferencial univariada y bivariada, a partir de los resultados de una encuesta realizada a jóvenes de la ciudad de Taichung. Entre los principales resultados del estudio destaca su gran predilección por escoger destinos en Asia u Oceanía o el alto grado de importancia que dan a las atracciones o paisajes naturales. Se concluye que los factores motivacionales de empuje y atracción analizados en el estudio son importantes para entender el comportamiento turístico de los jóvenes taiwaneses, pero no son suficientes para evidenciar las diferencias entre los perfiles turísticos de los millennials y centennials.
Recreation leadership. Administration of recreation services, The city as an economic factor. City promotion
In this article, we explore two effective means to communicate the concept of walkability - 1) visualization, and 2) descriptive statistics. We introduce the concept of walkability as measuring the quality of an urban space based on the distance needed to walk from that space to a range of different social, environmental, and economic amenities. We use Dublin city as a worked example and explore quantification and visualization of walkability of various areas of the city. We utilize the Google Map API and Tableau to visualize the less walkable areas across Dublin city and using WLS regression, we assess the effects of unwalkability on house prices in Dublin, thus quantifying the importance of walkable areas from an economic perspective.
City modeling and generation have attracted an increased interest in various applications, including gaming, urban planning, and autonomous driving. Unlike previous works focused on the generation of single objects or indoor scenes, the huge volumes of spatial data in cities pose a challenge to the generative models. Furthermore, few publicly available 3D real-world city datasets also hinder the development of methods for city generation. In this paper, we first collect over 3,000,000 geo-referenced objects for the city of New York, Zurich, Tokyo, Berlin, Boston and several other large cities. Based on this dataset, we propose AETree, a tree-structured auto-encoder neural network, for city generation. Specifically, we first propose a novel Spatial-Geometric Distance (SGD) metric to measure the similarity between building layouts and then construct a binary tree over the raw geometric data of building based on the SGD metric. Next, we present a tree-structured network whose encoder learns to extract and merge spatial information from bottom-up iteratively. The resulting global representation is reversely decoded for reconstruction or generation. To address the issue of long-dependency as the level of the tree increases, a Long Short-Term Memory (LSTM) Cell is employed as a basic network element of the proposed AETree. Moreover, we introduce a novel metric, Overlapping Area Ratio (OAR), to quantitatively evaluate the generation results. Experiments on the collected dataset demonstrate the effectiveness of the proposed model on 2D and 3D city generation. Furthermore, the latent features learned by AETree can serve downstream urban planning applications.
<p>In order to avoid the real economy development lags behind and the deterioration of ecological problems in the process of traditional urbanization, China has been promoting city-industry deep integration, but the connection between city-industry integration and green economic growth, especially the spatial effect, has not been systematically explained. Based on the panel data from 2007 to 2018, this paper constructs an evaluation index system and uses the SEEA method to measure city-industry integration (CII) level and green economy growth (GEG) level. Then, by employing spatial Durbin model and intermediary effect model, it further systematically investigates the spatial impact of CII on GEG and the potential mechanism. The study found that: (1) On the whole, CII shows “slow-steady integration” trend, but regional heterogeneity was obvious and accompanied by “slow gap expansion”. GEG experienced “sharp increase” with “polarization” characteristic. (2) CII can directly promote regional GEG (with a marginal effect of 0.689), more effectively than traditional urbanization, and CII has obvious spatial spillover effects on GEG in both “local effect” and “neighboring effect”. (3) Interestingly, technological innovation and consumption structure upgrading are significant mediating mechanisms. (4) The direct positive effect of CII shows the regional imbalance characteristic. Finally, the corresponding policy implications are put forward.</p>
AbstractRural areas are always exposed to serious risks and damages, which shows the importance of risk management and forecasting. Resilience is an approach that can help improve rural areas and their response in the face of crisis. In this study, the aim is to identify and analyze the factors affecting the economic and social resilience of rural areas in the form of a case study in Kermanshah. The research method is descriptive-analytical and based on data collection through the field approach. The data collection tool was a questionnaire. The structural and content validity of the questionnaire was approved and its reliability was also confirmed with a Cronbach's coefficient greater than 0.74. The statistical population of the research was formed by the heads of households in the villages with more than 100 households in the central part of Kermanshah city, which were a total of 2314 households. The sample size was determined through Cochran's formula, 330 household heads. The result of the test showed that the economic and social resilience of rural areas is significant at the level of less than 0.05 and according to the calculated average (2.386), their condition is evaluated as unfavorable. Among the 11 indicators of economic and social resilience, two indicators of damage with an average of 3.962, and then preparedness to deal with accidents among villagers with an average of 3.093 had an average status and the rest of the indicators were weak. Also, the results of the factor analysis confirm that the three factors of the prosperity of economic platforms and job creation, improvement of human and social capital, as well as the creation of facilities and income capacities, are the most influential factors in the resilience of rural areas.Keywords: Economic and Social Resilience, Rural Areas, Kermanshah County. IntroductionRural areas are not exempt from natural crises and possible damages. Today, rural areas are facing many problems and dilemmas, one of these problems is natural hazards that occur suddenly in villages. How to deal with these risks has led to the discussion of resilience against risks in societies today. Resilience indicators against damages and crises are one of the basic criteria in the process of planning and evaluating adaptation programs to the effects of natural hazards in rural areas. Evaluating and measuring the resilience of rural communities is one of the most important tools in diagnosing the stability of rural settlements when risks and crises occur. Rural areas are always exposed to serious risks and damages, which shows the importance of risk management and forecasting. Resilience is an approach that can help improve rural areas and their response in the face of crisis. This research aims to identify and analyze the factors affecting the economic and social resilience of rural areas as a case study in Kermanshah County. Materials and MethodsThe research method of this quantitative and applied study is based on the descriptive-analytical approach. The research data are the result of a survey study at the level of rural areas. The main tool of the research is the researcher's questionnaire, whose validity was confirmed by experts. Its reliability was also confirmed through Cronbach's alpha coefficient, which obtained a high value of 0.74 for different parts of the questionnaire. The statistical population of this research was formed by the heads of rural areas of more than 100 households in the central part of Kermanshah. According to the last census (2015), the population of these villages was 8210 people and 2314 households. The sample size was calculated using Cochran's formula to be 330 people at the level of household heads. SPSS software and appropriate statistical tests were used for data analysis. Research FindingsThe result of the test showed that except for the variable of dependence on a job with a significance level of 0.195, other economic variables were significant at a level of less than 0.05. Examining the significance direction using the average shows that the variables of the state of the cultivated area (3.139), dependence on a job (3/078), and the status of women's participation in household employment (3/472) were at a moderate level. In addition, the variables of the amount of damage caused to capital and assets (housing, livestock, etc.) with an average of 3.942, the vulnerability of income and assets with an average of 3.981, and willingness to receive a loan with an average of 4.003 were at an acceptable level. The result shows that other variables of economic resilience, such as the importance of savings and investment, the amount of access to production factors, the amount of assets and fixed capital, the areas of employment creation, etc., were poorly evaluated.The result of the sample t-test shows that all variables of social resilience in rural areas were significant at a level less than 0.05 and equal to 0.000. Examining the significance direction indicates that only the variables belonging to the village with an average of 3.487, ethnic belonging to the village with an average of 3.672, the situation and trend of migration from the village with an average of 3.700, and the physical and mental health of the villagers with an average of 3.690 are known to be in an average state compared to other variables of social resilience. The result of the test shows that other variables of social resilience, including membership in different groups of the village, participation in the village's common benefit activities, cooperation and interaction of the villagers towards each other, the situation and structure of the village population, knowledge and awareness of dealing with crisis, skills and the ability to deal with the crisis, and the existence of associations (communities) were at a weak and inappropriate level.The result of the test in the field of 6 indicators of economic resilience and 5 indicators of social resilience shows that all resilience indicators were significant at the level of less than 0.05. Examining the significance direction indicates that the average of all economic and social resilience indicators, except for the two indicators of damage and preparedness to deal with accidents, is lower than the average of the test (3), and therefore the resilience situation in rural areas is evaluated as weak. Examining the total resilience in rural areas also confirms this point because the result of the test shows that the level of resilience in rural areas is less than 0.05 and the average is 2.386.Also, the results showed that rural areas (20 villages) in terms of damage indicators, disaster preparedness among villagers, economic capital and assets, employment, cost and income, benefit from banking resources, capacity to return to employment and income conditions, social belonging, social participation, resources and human capital, and the capacity of spontaneous and people's institutions have no significant difference. Discussion of Results and ConclusionThe result of the study showed that the state of resilience in rural areas is poorly evaluated. This assessment also shows that all villages have the same conditions in terms of economic and social resilience. Also, the result showed that three main or macro factors are effective in the resilience of rural areas and their improvement. These three factors are the prosperity of economic platforms and job creation, the promotion of human and social capital, as well as the creation of facilities and income capacities. Therefore, planning should be in line with emphasizing and promoting these factors by identifying influential indicators in this field. ReferencesPersian References- Dadashpour, H., & Adeli, Z. (2014). Measuring resilience capacities in Qazvin urban complex. Journal of Crisis Management, 4(8), 73-84.- Haddad, M., & Sadeghi, H. (2020). 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A lack of financial access, which is often an issue in many central-city U.S. neighborhoods, can be linked to higher interest rates as well as negative health and psychological outcomes. A number of analyses of "banking deserts" have also found these areas to be poorer and less White than other parts of the city. While previous research has examined specific cities, or has classified areas by population densities, no study to date has examined a large set of individual cities. This study looks at 319 U.S. cities with populations greater than 100,000 and isolates areas with fewer than 0.318 banks per square mile based on distances from block-group centroids. The relative shares of these "deserts" appears to be independent of city population across the sample, and there is little relationship between these shares and socioeconomic variables such as the poverty rate or the percentage of Black residents. One plausible explanation is that only a subset of many cities' poorest, least White block groups can be classified as banking deserts; nearby block groups with similar socioeconomic characteristics are therefore non-deserts. Outside of the Northeast, non-desert areas tend to be poorer than deserts, suggesting that income- and bank-poor neighborhoods might not be as prevalent as is commonly assumed.
The use of cars in cities has many negative impacts on its population, including pollution, noise and the use of space. Yet, detecting factors that reduce automobile dependency is a serious challenge, particularly across different regions. Here we model the use of different modes of transport in a city by aggregating active mobility (A), public transport (B) and cars (C), thus expressing the modal share of a city by its ABC triplet. Data for nearly 800 cities across 60 countries is used to model car use and its relationship with city size and income. Our findings suggest that outside the US, longer distances experienced in large cities reduce the propensity of active mobility and of cars, but public transport is more prominent. For cities in the US, roughly 90\% of its mobility depends on cars, regardless of city size. Further, income is strongly related to automobile dependency. Results show that a city with twice the income has 37\% more journeys by car.
Omar Cheikhrouhou, Ichrak Amdouni, Khaleel Mershad
et al.
Cybersecurity is an inherent characteristic that should be addressed before the large deployment of smart city applications. Recently, Blockchain appears as a promising technology to provide several cybersecurity aspects of smart city applications. This paper provides a comprehensive review of the existing blockchain-based solutions for the cybersecurity of the main smart city applications, namely smart healthcare, smart transportation, smart agriculture, supply chain management, smart grid, and smart homes. We describe the existing solutions and we discuss their merits and limits. Moreover, we define the security requirements of each smart city application and we give a mapping of the studied solutions to these defined requirements. Additionally, future directions are given. We believe that the present survey is a good starting point for every researcher in the fields of cybersecurity, blockchain, and smart cities.
Eduardo Graells-Garrido, Feliu Serra-Burriel, Francisco Rowe
et al.
As cities expand, human mobility has become a central focus of urban planning and policy making to make cities more inclusive and sustainable. Initiatives such as the "15-minutes city" have been put in place to shift the attention from monocentric city configurations to polycentric structures, increasing the availability and diversity of local urban amenities. Ultimately they expect to increase local walkability and increase mobility within residential areas. While we know how urban amenities influence human mobility at the city level, little is known about spatial variations in this relationship. Here, we use mobile phone, census, and volunteered geographical data to measure geographic variations in the relationship between origin-destination flows and local urban accessibility in Barcelona. Using a Negative Binomial Geographically Weighted Regression model, we show that, globally, people tend to visit neighborhoods with better access to education and retail. Locally, these and other features change in sign and magnitude through the different neighborhoods of the city in ways that are not explained by administrative boundaries, and that provide deeper insights regarding urban characteristics such as rental prices. In conclusion, our work suggests that the qualities of a 15-minutes city can be measured at scale, delivering actionable insights on the polycentric structure of cities, and how people use and access this structure.