Resumo As áreas centrais tradicionais de algumas cidades brasileiras, convertidas em territórios privilegiados para a promoção imobiliária a partir de políticas públicas estruturantes e de incentivos fiscais, têm recentemente atraído investimentos para a construção de empreendimentos de “unidades compactas”, do tipo estúdio ou de 1 quarto, a serem ofertados para a locação via plataformas digitais. Dissolvendo as fronteiras entre moradia e hospedagem e promovendo o conceito do “aluguel descomplicado”, a nova oferta imobiliária visa atender tanto a investidores quanto a moradores transitórios. A partir do detalhamento do caso do Recife, a pesquisa aborda as inovações no mercado imobiliário decorrentes da consolidação do novo mecanismo de oferta via plataformas, assim como as repercussões dessa dinâmica sobre áreas urbanas concentradoras de tais empreendimentos.
Objective: To investigate the association between county-level social capital and screening mammography rates among older women in the United States. Methods: This cross-sectional ecological study included 2765 U.S. counties, using 2018 county-level screening mammography rates among female Medicare enrollees aged 67–69 as the outcome. Social capital data were obtained from the 2018 Social Capital Project, including indices for Family Unity, Institutional Health, Collective Efficacy, and Community Health. Multivariable log-binomial regression analyses were conducted to estimate adjusted prevalence ratios (aPRs) and confidence intervals for “high” mammography rates (top 10 % nationally), controlling for county-level demographic and healthcare covariates. Stratified analyses examined associations among metropolitan and nonmetropolitan counties. Results: Mammography screening rates ranged from 17 % to 64 %, with a mean of 41 %. Strong positive associations were observed between social capital and mammography rates (Q4 vs. Q1: aPR = 2.29, 95 % CI: 1.20–4.36), particularly for the dimensions of Community Health (Q4 vs. Q1: aPR = 1.99, 95 % CI = 1.25–3.17) and Institutional Health (Q4 vs. Q1: aPR = 4.31, 95 % CI = 2.40–7.75). These associations were strongest among nonmetropolitan counties. No significant associations were found for Family Unity or Collective Efficacy. Conclusions: County-level social capital, specifically community and institutional health, is significantly associated with higher mammography screening rates, particularly in non-metropolitan areas. These findings suggest that enhancing public trust and community engagement may improve screening behaviors. Future research should explore the role of social capital at multiple levels and its influence on various cancer screening behaviors.
Barbara Pawłowska, Agnieszka Szmelter-Jarosz , Beata Chmiel
Urbanisation, defined as the process of increasing urban population and the development of cities, is a global phenomenon with diverse directions and scenarios across different world regions, including Europe. Currently, 50% of the world’s population lives in cities; by 2050, it will be nearly 68% (Multiple sources compiled by World Bank, 2024). In Europe, 80% of the population already resides in urban areas. However, urbanisation is a complex process with many recognised benefits stemming from well-developed urban areas, but also significant challenges and risks. As a result of contemporary transformations, a reverse phenomenon is being observed. In many regions, suburban areas are expanding, leading to urban sprawl into rural territories, often without adequate spatial planning and transport infrastructure. Increasing emphasis is placed on creating environmentally friendly, inclusive cities with efficient public transportation, green spaces, and sustainable construction. Assessing public transport user satisfaction is a key element in supporting efforts toward sustainable regional development. This article aims to examine the opinions of Tri-City (Gdansk, Sopot, Gdynia) residents regarding the functioning of public transport. Analysing passenger feedback allows for identifying the strengths and weaknesses of the urban transport system, which is essential for implementing effective strategies to improve service quality. Surveys with city users of the Tri-City Metropolitan Area provide valuable insights into the current state of urban transport and highlight areas requiring improvement.
Abstract Accurate information on urban tree species composition is critical for urban green space ecosystem management. However, achieving large-scale, high-precision species identification in complex metropolitan environments remains challenging. This study assessed the potential of medium-resolution multi-temporal optical imagery combined with airborne LiDAR for tree species classification in large heterogeneous urban areas (> 5000 km²). The results indicate that precise large-scale identification of urban tree species distribution is feasible by integrating multi-seasonal Sentinel-2 imagery with airborne LiDAR data based on a Random Forest hierarchical classification model. The overall classification accuracies for deciduous broadleaf species and evergreen broadleaf species were 63.32% and 76.77%, respectively. Multi-temporal spectra were the primary explanatory variables, with spring bands significantly affecting the classification of deciduous broadleaf species. For evergreen broadleaf species, each season has its own dominant spectral information. Classifications combining data from three seasons outperformed single- or two-season combinations. The incorporation of LiDAR-derived metrics improved the classification results for most species, with accuracy increases of up to 18.75% point for deciduous broadleaf species. Overall, the results demonstrate the effectiveness of combining medium-resolution multi-temporal optical imagery with LiDAR data for urban tree species classification, laying a foundation for quantifying ecosystem services provided by urban trees through remote sensing.
The overdamped Josephson junction in superconductivity theory can be modeled by the family of dynamical systems on the torus, which is known as the RSJ model. This family admits an equivalent description by a family of second-order differential equations: special double confluent Heun equations. In the present paper, we construct two new families of dynamical systems on torus that can be equivalently described by a family of general Heun equations (GHE), with four singular points, and confluent Heun equations, with three singular points. The first family, related to GHE, is a deformation of the RSJ model, which will be denoted by dRSJ. The phase-lock areas of a family of dynamical systems on the torus are those level subsets of the rotation number function that have nonempty interiors. It is known that for the RSJ model, the rotation number quantization effect occurs: phase-lock areas exist only for integer rotation number values. Moreover, each phase-lock area is a chain of domains separated by points. Those separation points that do not lie on the abscissa axis are called constrictions. In the present paper, we study phase-lock areas in the new family dRSJ. The quantization effect remains valid in this family. On the other hand, we show that in the new family dRSJ the constrictions break down.
Sunday Stephen Ajemunigbohun, Kudirat Adeola Banjo, Taiwo Olarinre Oluwaleye
With the increasing prevalence of uninsured vehicles in urban areas, motorists’ behaviours on pedestrian safety are crucial for developing effective road safety strategies. This study investigated the happenings around uninsured motorists’ risk attitudes and pedestrian road safety in metropolitan Lagos, Nigeria. Using the survey approach cum the two-way sampling techniques comprised of purposive and convenience, data were gathered to analyse the behavioural dispositions of uninsured motorists and their implications on pedestrian road safety. The study adopted a structured questionnaire as a research instrument for data collection from a sample population of 209. The data analytical employed was descriptive statistics comprised of simple frequency percentages presented in tabular form and bar chart description. Findings revealed, based on pedestrian opinions, that uninsured motorists display riskier driving behaviours, such speeding and reckless driving pattern; which was found prevalent among commercial uninsured motorists. In addition, insufficient implementation of insurance regulation and socio-economic factors contributed to the proliferation of uninsured vehicles. The study also showcased the descriptive analysis of uninsured motorists’ risk attitudes towards pedestrian road safety. Further finding presented a descriptive analysis of pedestrians’ road safety metrics on Lagos roads. Then, the study accentuates the urgent need for comprehensive policy intervention targeting uninsured motorists, including stricter application of insurance laws, public awareness campaigns, enhanced infrastructure to improve pedestrian safety in urban environment, like metropolitan, Lagos, Nigeria and in similar contexts in other African cities and beyond. Thus, insurance practitioners, especially motor insurance providers, should synergise their efforts to improve the accessibility and affordability of insurance for motorists, particularly, the low-income individuals; by creating flexible payment options, and subsidising insurance premiums. Lastly, local communities should engage with other stakeholders in the transport industry to ensure road safety culture, promoting responsible driving behaviour and encouraging compliance with insurance regulation.
In recent decades, the increasing frequency of urban fires, driven by urban functional enhancements and climate change, has posed a growing threat to metropolitan sustainability. This study investigates the temporal and spatial characteristics of fire incidents in Shanghai from 2019 to 2023. Using satellite fire point data and official government records, kernel density analysis and wavelet analysis were employed to analyze the time series and spatial distribution of fire data. Subsequently, eleven primary factors influencing urban fire occurrence were identified, encompassing probability, regional characteristics, and hazard sources. A combined methodology of subjective and objective weights with game theory was used to generate a fire risk assessment at a 1 × 1 km<sup>2</sup> grid scale. Furthermore, the spatial distribution characteristics of the assessments were analyzed. The results reveal that the downtown area exhibits the highest intensity of urban fires in terms of spatial domain, with a decreasing intensity towards the suburbs. Temporally, fire frequency demonstrates significant periodicity at an 18a time scale, while clear seasonal fluctuations and periodicity are observed at a 16-22a time scale, with higher occurrences in spring and winter. The study identifies typical aggregation patterns of urban fires, with high-risk centers in downtown Shanghai. Considering the impact of climate change and human activities, high-risk areas may gradually expand to adjacent urban suburbs, presenting a concerning future scenario. By examining the dual attributes of “combustibles and fireproof space” within urban greening systems, this research offers recommendations for the future strategies of disaster prevention and mitigation of green systems in Shanghai.
If neuroscientists were asked which brain area is responsible for object recognition in primates, most would probably answer infero-temporal (IT) cortex. While IT is likely responsible for fine discriminations, and it is accordingly dominated by foveal visual inputs, there is more to object recognition than fine discrimination. Importantly, foveation of an object of interest usually requires recognizing, with reasonable confidence, its presence in the periphery. Arguably, IT plays a secondary role in such peripheral recognition, and other visual areas might instead be more critical. To investigate how signals carried by early visual processing areas (such as LGN and V1) could be used for object recognition in the periphery, we focused here on the task of distinguishing faces from non-faces. We tested how sensitive various models were to nuisance parameters, such as changes in scale and orientation of the image, and the type of image background. We found that a model of V1 simple or complex cells could provide quite reliable information, resulting in performance better than 80% in realistic scenarios. An LGN model performed considerably worse. Because peripheral recognition is both crucial to enable fine recognition (by bringing an object of interest on the fovea), and probably sufficient to account for a considerable fraction of our daily recognition-guided behavior, we think that the current focus on area IT and foveal processing is too narrow. We propose that rather than a hierarchical system with IT-like properties as its primary aim, object recognition should be seen as a parallel process, with high-accuracy foveal modules operating in parallel with lower-accuracy and faster modules that can operate across the visual field.
Pierre-Alexandre Bliman, Nga Nguyen, Nicolas Vauchelet
The Sterile Insect Technique (SIT) is one of the sustainable strategies for the control of disease vectors, which consists of releasing sterilized males that will mate with the wild females, resulting in a reduction and, eventually a local elimination, of the wild population. The implementation of the SIT in the field can become problematic when there are inaccessible areas where the release of sterile insects cannot be carried out directly, and the migration of wild insects from these areas to the treated zone may influence the efficacy of this technique. However, we can also take advantage of the movement of sterile individuals to control the wild population in these unreachable places. In this paper, we derive a two-patch model for Aedes mosquitoes where we consider the discrete diffusion between the treated area and the inaccessible zone. We investigate two different release strategies (constant and impulsive periodic releases), and by using the monotonicity of the model, we show that if the number of released sterile males exceeds some threshold, the technique succeeds in driving the whole population in both areas to extinction. This threshold depends on not only the biological parameters of the population but also the diffusion between the two patches.
Luiz Carlos Day Gama, Ana Hermeto, Philipe Scherrer Mendes
We aim to study the role of labor market mismatch in the context of international migration. Mismatch employment occurs when high-skill workers are employed in occupations that do not need such education and vice versa. The results show: i) undereducation is on average lower among immigrants, while overeducation is higher among immigrants; ii) immigrants are more likely to be employed than natives; iii) mismatch is important in explaining wages; iv) there are differences in occupational mismatch effects; v) the immigrant’s place of origin is not important to explain occupation status but it is very important to explain differences in wages.
This work presents a framework for assessing the socio-physical disruption of critical infrastructure accessibility using the example of Greater Jakarta, a metropolitan area of the Indonesian city. The first pillar of the framework is damage quantification based on the real flood event in 2020. Within this pillar, the system network statistics before and shortly after the flood were compared. The results showed that the flood impeded access to facilities, distorted transport connectivity, and increased system vulnerability. Poverty was found to be negatively associated with surface elevation, suggesting that urbanization of flood-prone areas has occurred. The second pillar was a flood simulation. Our simulations identified the locations and clusters that are more vulnerable to the loss of access during floods, and the entire framework can be applied to other cities and urban areas globally and adapted to account for different disasters that physically affect urban infrastructure. This work demonstrated the feasibility of damage quantification and vulnerability assessment relying solely on open and publicly available data and tools. The framework, which uses satellite data on the occurrence of floods made available by space agencies in a timely manner, will allow for rapid ex post investigation of the socio-physical consequences of disasters. It will save resources, as the analysis can be performed by a single person, as opposed to expensive and time-consuming ground surveys. Ex ante vulnerability assessment based on simulations will help communities, urban planners, and emergency personnel better prepare for future shocks.
Mauricio-René Herrera-Marín, Francisco Vergara-Perucich, Carlos Aguirre-Núñez
et al.
The spread of COVID-19 has been extensively studied, but the intricate dynamics of its transmission in interdependent and segregated urban areas, constrained by mobility restrictions, have not been completely understood yet. The pandemic's dynamic-adaptive nature implies that virus spread is influenced by diverse factors operating disparately in urban areas with distinct roles. This study investigates the dynamic spread patterns of COVID-19 in the Santiago Metropolitan Area (SMA), Chile, leveraging explanatory variables related to urban mobility, socio-spatial characteristics, segregation, and sanitary measures. Using publicly available mobility data, we used two indices—the Internal Mobility Index (capturing individual trips within a city’s commune), and the External Mobility Index (indicating trips crossing commune borders). These indices were derived from geolocation data recorded by the cellular telephone antenna network of the Telefónica company by tracking successive antenna transitions during trips. The analysis encompasses a three-stage pandemic pattern, corresponding to periods before, during, and after an initial lockdown in the pandemic's first year. Elastic-Net-Penalty regression models, skillful in both feature selection and managing highly correlated predictors while maintaining the interpretability of the models, are used. These models employ a combination of L1 (ridge) and L2 (lasso) regularized log-likelihood optimization. The ridge penalty functions by contracting the coefficients of correlated predictors, pulling them closer to each other. In contrast, the lasso method tends to choose one predictor and exclude the others. The analysis with these models unveils influences of various explanatory variable subsets throughout the pandemic. Importantly, the study provides evidence justifying the suboptimal outcomes of the dynamic quarantine imposed by authorities. Mobility restrictions were implemented without considering the intricate contextual factors, thus impacting vulnerable areas of the city adversely.
Eriks Klotins, Michael Unterkalmsteiner, Tony Gorschek
Background - Startup companies are becoming important suppliers of innovative and software intensive products. The failure rate among startups is high due to lack of resources, immaturity, multiple influences and dynamic technologies. However, software product engineering is the core activity in startups, therefore inadequacies in applied engineering practices might be a significant contributing factor for high failure rates. Aim - This study identifies and categorizes software engineering knowledge areas utilized in startups to map out the state-of-art, identifying gaps for further research. Method - We perform a systematic literature mapping study, applying snowball sampling to identify relevant primary studies. Results - We have identified 54 practices from 14 studies. Although 11 of 15 main knowledge areas from SWEBOK are covered, a large part of categories is not. Conclusions - Existing research does not provide reliable support for software engineering in any phase of a startup life cycle. Transfer of results to other startups is difficult due to low rigor in current studies.
In China's Greater Bay Area (Guangdong-Hong Kong-Macao), the increasing use of Blockchain technology in financial services has the potential to generate benefits for many stakeholders. Blockchains are known for their distinctive features, such as decentralized architecture, tamper-proof data structures, and traceable transactions. These features make Blockchain a preferred choice of platform for developing applications in financial service areas. Meanwhile, some questions have been raised regarding Blockchain's suitability to compete with or even replace existing financial systems. This paper provides insights into the current progress of Blockchain applications in insurance, banking, payments, asset trading, loans, remittances, the Internet of Things (IoT) for the finance industry, financial inclusions, and enterprise-level interaction in finance and governance. We review the barriers to widespread Blockchain adoption, especially the risks when transaction fees dominate mining rewards. By comparing the emerging Blockchain technologies and incentive issues related to real-world applications, we hope that this paper can serve as a valuable source of reference for Blockchain researchers and developers in financial service areas.
Kelvin L. T. Fung, Simon T. Perrault, Michael T. Gastner
A contiguous area cartogram is a geographic map in which the area of each region is proportional to numerical data (e.g., population size) while keeping neighboring regions connected. In this study, we investigated whether value-to-area legends (square symbols next to the values represented by the squares' areas) and grid lines aid map readers in making better area judgments. We conducted an experiment to determine the accuracy, speed, and confidence with which readers infer numerical data values for the mapped regions. We found that, when only informed about the total numerical value represented by the whole cartogram without any legend, the distribution of estimates for individual regions was centered near the true value with substantial spread. Legends with grid lines significantly reduced the spread but led to a tendency to underestimate the values. Comparing differences between regions or between cartograms revealed that legends and grid lines slowed the estimation without improving accuracy. However, participants were more likely to complete the tasks when legends and grid lines were present, particularly when the area units represented by these features could be interactively selected. We recommend considering the cartogram's use case and purpose before deciding whether to include grid lines or an interactive legend.
The problems that exist in implementing a sampling design for socio-economic surveys in remote areas in Indonesia are high cost of the survey, low response rate, and less accurate. Therefore, the sampling design needs to be developed, one of which is to improve the efficiency of the stratification procedure. Stratification of census block in remote areas can be developed by combining the strata of welfare concentration and the strata of geographic difficulty by simulating the various alternatives number of strata and the various alternatives sample allocation. The strata of welfare concentration and the strata of geographic difficulty are constructed by Polychoric Principal Component Analysis. The strata of welfare concentration aim to improve statistical efficiency, while the strata of geographic difficulty are used to improve cost efficiency. The estimation procedure is performed at the domain level and population level. The simulation study focus on Papua Province by using the 2010 Population Census data and the 2011 Village Potency data. Some sampling scenarios can be categorized into four quadrants, the first quadrant with small sampling variance and low cost, the second quadrant with big sampling variance and low cost, the third quadrant with big sampling variance and high cost, and the fourth quadrant with small sampling variance and high cost. Based on these simulation results, several alternative scenarios of efficient stratification with small sampling variance and low cost of the survey are obtained.
Land-use change is an important contributor to atmospheric carbon emissions. Taking Jinhua city in eastern China as an example, this study analyzed the effects on carbon emissions by land-use changes from 2005 to 2018. Then, carbon emissions that will be produced in Jinhua in 2030 were predicted based on the land-use pattern predicted by the CA-Markov model. Finally, a low-carbon optimized land-use pattern more consistent with the law of urban development was proposed based on the prediction and planning model used in this study. The results show that (1) from 2005 to 2018, the area of land used for construction in Jinhua continued to increase, while woodland and cultivated land areas decreased. Carbon emissions from land use rose at a high rate. By 2018, carbon emissions had increased by 1.9 times compared to 2015. (2) During the 2010–2015 period, the total concentration of carbon emissions decreased due to decreases in both the rate of growth in construction land and the rate of decline in a woodland area, as well as an adjustment of the energy structure and the use of polluting fertilizer and pesticide treatments. (3) The carbon emissions produced with an optimal land-use pattern in 2030 are predicted to reduce by 19%. The acreage of woodland in Jinhua’s middle basin occupied by construction land and cultivated land is predicted to reduce. The additional construction land will be concentrated around the main axis of the Jinhua-Yiwu metropolitan area and will exhibit a characteristic ribbon-form with more distinct clusters. The optimized land-use pattern is more conducive to carbon reduction and more in line with the strategy of regional development in the study area. The results of this study can be used as technical support to optimize the land-use spatial pattern and reduce urban land’s contribution to carbon emissions.