We study gravitational algebras on spacetimes with two extremal surfaces. In the example of a long wormhole with two asymptotic AdS boundaries and two compact extremal surfaces, we discuss the assignment of gravitational algebras to various regions bounded by the extremal surfaces and/or asymptotic boundaries. Using the split property, we construct type II algebras from the crossed product in the left exterior, right exterior, the middle ``python's lunch'' region, and their complement regions. We also study the case where only the area sum operator or area difference operator is included as part of the gravitational algebra. This can be achieved by picking the appropriate microcanonical ensemble, and these gravitational algebras can either be type II or type III depending on the region. In the case where we include only the area difference mode, the crossed product gives rise to a weight that restricts to a trace on the middle region. Differences of relative entropies with respect to this weight give differences in generalized entropies. This provides an algebraic understanding of the order parameter that controls the phase transitions between entanglement wedges. We emphasize the role of operator-valued weights used in our construction.
Brendan G Dillon, Hugh P Possingham, Matthew H Holden
Several international agreements have called for the rapid expansion of protected areas to halt biodiversity declines. However, recent research has shown that expanding protected areas may be less cost-effective than redirecting resources towards threat management in existing reserves. These findings often assume that threats are homogeneously distributed in the landscape. In some cases, threats are more concentrated near the edge of protected areas. As protected areas expand, core habitat in the centre expands more rapidly than its edge, potentially creating a refuge from threats. In this paper, we present a framework linking protected area expansion and threat management to extinction risk, via their impact on population carrying capacity and growth rate within core and edge habitats. We demonstrate the framework using a simple population model where individuals are uniformly distributed in a circular protected area threatened by poachers who penetrate the protected area to a fixed distance. We parameterise the model for Peter's Duiker (Cephalophus callipygus) harvested for food in the dense undergrowth of African forests using snares. Expanding protected areas can reduce extinction risk more effectively compared to an equivalent investment in snare removal for larger protected areas that already sustain core unhunted habitat. Our results demonstrate the importance of protected area expansion in buffering susceptible populations from fixed hunting pressure restricted to protected area edges. However, for cases where threats, wildlife, and managers respond to each other strategically in space, the relative importance of expansion versus increased management remains a significant open problem.
Climate change and air pollution are intrinsically interconnected as carbon dioxide and air pollutants are co-emitted during fossil fuel combustion. Low-carbon policies, aimed at mitigating carbon emissions, are also anticipated to yield co-benefits for air quality; however, the extent to which regional low-carbon policies can effectively achieve significant reductions in air pollutant levels remains uncertain. In China, the implementation of the low-carbon city pilot (LCCP) policy has reduced carbon emissions, but further research is needed to examine its effectiveness regarding achieving air quality co-benefits. Adopting a difference-in-differences model with a 19-year national database of air quality, this study examines whether the LCCP policy improves air quality in China’s metropolitan areas and explores how these policy initiatives address their air pollution challenges. The results indicate that, following the implementation of the LCCP policy, the mean, maximum, and standard deviation of the AQI in pilot cities decreased significantly by 9.3%, 20.8%, and 19.8%, respectively, compared to non-pilot cities. These results suggest that the LCCP policy significantly improves air quality and provide evidence that this improvement is facilitated by advancements in green technology, industrial restructuring, and the optimization of urban planning and landscape design.
Urban development is the planned growth of cities that takes into account ecological issues, the needs of urban life, social and technical equipment standards, and quality of life. However, as a result of policies implemented by decision-makers and users, both planned and unplanned, urban space is expanding spatially outwards from the city, while also experiencing densification in vacant areas within the city and functional transformations in land use. This process, known as urban sprawl, has been intensely debated over the past century. Making the negative effects of urban sprawl measurable and understandable from a scientific perspective is critically important for sustainable urban planning and management. Transportation surfaces hold a significant share in the land use patterns of expanding cities in physical space, and accessibility is one of the main driving forces behind land use change. Therefore, the most significant consequence of urban sprawl is the increase in urban mobility, which is shaped by the needs of urban residents to access urban functions. This increase poses risk factors for the planning period in terms of time, cost, and especially environmental impact. Urban space has a dynamic and complex structure. Planning is based on being able to guess how this structure will change over time. At first, geometric models were used to study cities, but as time went on and the network of relationships became more complicated, more modern and technological methods were needed. Artificial Neural Networks, Support Vector Machines, Agent-Based Models, Markov Chain Models, and Cellular Automata, developed using computer-aided design technologies, can be cited as examples of these approaches. In this study, the temporal change in urban sprawl and its relationship with influencing factors will be revealed using the SLEUTH model, which is one of the cellular automata-based urban simulation models. Erzurum, one of the medium-sized metropolitan cities that gained importance after the conversion of provincial borders into municipal borders with the Metropolitan Law No. 6360, has been selected as the case study area for this research. The urban sprawl process and determining factors of Erzurum will be analyzed using the SLEUTH model. By creating a simulation model of the current situation within the specified time periods and generating future scenarios, the aim is to develop planning decisions with sustainable, ecological, and optimal size and density values.
Advanced Air Mobility (AAM) presents an emerging alternative to traditional car driving for commuting in metropolitan areas. However, its feasibility has not been thoroughly studied nor well understood at the operational level. Given that AAM has not been in place, this study explores the economic, energy, and environmental feasibility of AAM for commuting at an early stage of AAM deployment. We propose a time-expanded network model to characterize the dynamics of eVTOL operations between a vertiport pair in different states: in-service flying, relocation flying, charging, and parking, while respecting various operational and commuter time window constraints. By jointly considering eVTOL flying with vertiport access and egress and using real-world data, we demonstrate an application of the model in the Chicago metropolitan area in the US. Different vertiport pairs and eVTOL aircraft models are investigated. We find substantial travel time saving if commuting by AAM. While vehicle operating cost will be higher using eVTOLs than using auto, the generalized travel cost will be less for commuters. On the other hand, with current eVTOL power requirement, the energy consumption and CO2 emissions of AAM will be greater than those of auto driving, with an important contributor being the significance presence of empty flights relocation. These findings, along with sensitivity analysis, shed light on future eVTOL development to enhance the competitiveness of AAM as a viable option for commuting.
Transportation and communications, Transportation engineering
We propose MESA and DMESA as novel feature matching methods, which utilize Segment Anything Model (SAM) to effectively mitigate matching redundancy. The key insight of our methods is to establish implicit-semantic area matching prior to point matching, based on advanced image understanding of SAM. Then, informative area matches with consistent internal semantic are able to undergo dense feature comparison, facilitating precise inside-area point matching. Specifically, MESA adopts a sparse matching framework and first obtains candidate areas from SAM results through a novel Area Graph (AG). Then, area matching among the candidates is formulated as graph energy minimization and solved by graphical models derived from AG. To address the efficiency issue of MESA, we further propose DMESA as its dense counterpart, applying a dense matching framework. After candidate areas are identified by AG, DMESA establishes area matches through generating dense matching distributions. The distributions are produced from off-the-shelf patch matching utilizing the Gaussian Mixture Model and refined via the Expectation Maximization. With less repetitive computation, DMESA showcases a speed improvement of nearly five times compared to MESA, while maintaining competitive accuracy. Our methods are extensively evaluated on five datasets encompassing indoor and outdoor scenes. The results illustrate consistent performance improvements from our methods for five distinct point matching baselines across all datasets. Furthermore, our methods exhibit promise generalization and improved robustness against image resolution variations. The code is publicly available at https://github.com/Easonyesheng/A2PM-MESA.
Random tensor networks (RTNs) have proved to be fruitful tools for modelling the AdS/CFT correspondence. Due to their flat entanglement spectra, when discussing a given boundary region $R$ and its complement $\bar R$, standard RTNs are most analogous to fixed-area states of the bulk quantum gravity theory, in which quantum fluctuations have been suppressed for the area of the corresponding HRT surface. However, such RTNs have flat entanglement spectra for all choices of $R, \bar R,$ while quantum fluctuations of multiple HRT-areas can be suppressed only when the corresponding HRT-area operators mutually commute. We probe the severity of such obstructions in pure AdS$_3$ Einstein-Hilbert gravity by constructing networks whose links are codimension-2 extremal-surfaces and by explicitly computing semiclassical commutators of the associated link-areas. Since $d=3,$ codimension-2 extremal-surfaces are geodesics, and codimension-2 `areas' are lengths. We find a simple 4-link network defined by an HRT surface and a Chen-Dong-Lewkowycz-Qi constrained HRT surface for which all link-areas commute. However, the algebra generated by the link-areas of more general networks tends to be non-Abelian. One such non-Abelian example is associated with entanglement-wedge cross sections and may be of more general interest.
This paper explores the causal impact of education opportunities on rural areas by exploiting the higher education expansion (HEE) in China in 1999. By utilizing the detailed census data, the cohort-based difference-in-differences design indicates that the HEE increased college attendance and encouraged more people to attend senior high schools and that the effect is more significant in rural areas. Then we apply a similar approach to a novel panel data set of rural villages and households to examine the effect of education opportunities on rural areas. We find contrasting impacts on income and life quality between villages and households. Villages in provinces with higher HEE magnitudes underwent a drop in the average income and worse living facilities. On the contrary, households sending out migrants after the HEE experienced an increase in their per capita income. The phenomenon where villages experienced a ``brain drain'' and households with migrants gained after the HEE is explained by the fact that education could serve as a way to overcome the barrier of rural-urban migration. Our findings highlight the opposed impacts of education opportunities on rural development and household welfare in rural areas.
Urban tree canopies are a vital component of green infrastructure, especially in the context of the accelerating urban heat island effect and global climate change. Quantifying urban canopy cover in relation to land use and land cover changes is therefore crucial. However, accurately evaluating visual changes remains a challenge. In this study, we introduced the Urban Cover View Factor (VF) and Potential Influence Intensity Grade (PIIG) for tree canopy (TC) mapping using airborne Light Detection and Ranging (LiDAR) remote-sensing three-dimensional point clouds (3DPCs) from the Incheon metropolitan area, South Korea. The results demonstrated that airborne LiDAR 3DPCs effectively segmented non-sky urban cover views. Furthermore, the PIIG map, derived from the TC VF map, showed a significant correlation between surface heat risks and energy consumption patterns. Areas with lower PIIG grades tended to have higher energy consumption and greater vulnerability to surface heat risks, while areas with higher PIIG grades exhibited the opposite trend. Nevertheless, further exploration of complex urban cover and the collection of sufficient ground-based evidence is crucial for practical PIIG application. Further remote sensing research should support the management of urban tree canopies and urban agriculture to promote sustainable urban greening in response to evolving environmental needs.
Continuous evaluation and monitoring of long-term energy usage and carbon emissions are essential for developing, implementing, and assessing regional carbon reduction efforts. This study presents a spatiotemporal analysis of carbon emission trends in the Yangtze River Delta Urban Agglomeration (YRDUA) from 1992 to 2019. Researchers used nighttime light data from the Defense Meteorological Satellite Program's Operational Linescan System (DMSP/OLS) and the National Polar-orbiting Partnership's Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) to assess the evolution of carbon emission patterns. Advanced spatial analysis methods, including geographic autocorrelation, geographical panel modeling, and spatial Markov chains, were applied to explore the spatial impacts, processes, and regional context of these trends. The results show: (1) Carbon emissions in the YRDUA increased by 262.56 %, with high-emission spheres and axial expansion. High-high emission clusters emerged in metropolitan areas, while low-low clusters formed in peripheral mountain regions. (2) Carbon emission types were stable (66.5 %), but 17.6 % showed higher emissions transitioning to lower, particularly in northeast Jiangsu. (3) The broader regional background had a stronger influence on the spatial impacts of carbon emissions than nearest neighbor effects, enhancing both outlier convergence and “club convergence” among similar regions. (4) Spatiotemporal patterns were shaped by the lock-in effect in low-carbon areas and spillover effects in high-carbon areas, with economic scale and industrial structure as key drivers. This study provides crucial insights for regional carbon reduction strategies in the YRDUA.
Abstract Background Health literacy has been linked to positive attitudes toward COVID-19 preventive measures among adolescents and young- or middle-aged adult populations. This study examined the relationship between health literacy and attitudes toward COVID-19 preventive measures among non-English speaking Korean American older adults and their caregivers. The study additionally investigated how sociodemographic characteristics were associated with attitudes. Methods COVID-19 survey data was collected from potential participants for an ongoing randomized controlled trial involving both Korean American older adults and their caregivers in the Baltimore-Washington and the New York Metropolitan areas (ClinicalTrials.gov Identifier: NCT03909347). Korean American older adults with normal cognition and their caregivers were allowed to participate in the survey. We used latent profile analysis to find unique clusters of participants with a similar pattern of responses to attitudes toward COVID-19 preventive measures. Based on the analysis, we employed multinomial logistic regression to investigate how health literacy and sociodemographic characteristics were associated with the clusters. Results We found three clusters based on participant responses to COVID-19 preventive measures—Positive, Negative, or Mixed. Health literacy was not associated with COVID-19 related attitudes in the study sample. Men were 2.37 times more likely to be categorized as Mixed than having Positive Attitudes compared to women. The odds of a person living in the New York metropolitan area being categorized as having Mixed Attitudes compared to Positive Attitudes were also 2.67 times more than for a person living in the Baltimore-Washington area. Conclusions Differences in attitudes toward COVID-19 preventive measures were found among sociodemographic variables but not health literacy. Investigating what information channels or methods drive perception of public health information such as COVID-19 may help identify effective dissemination strategies for non-English speaking Korean older adults.
This study aims to present the meaningful implications of introducing a tramway as a new mode of transportation in the Daejeon Metropolitan Area, a major metropolitan area in South Korea. An efficiency comparison by data envelopment analysis (DEA) was carried out, using variables selected from the 2021 Public Transportation Investigation by the Korea Transportation Safety Authority (KTSA) (2021), and the ‘Guidelines for selecting new transportation means’ announced by the Ministry of Land, Infrastructure, and Transport in 2021. As a result, the efficiency of public transportation in major metropolitan areas outside of the capital region was higher than in the capital metropolitan area. In particular, the Daejeon Metropolitan Area ranked high in efficiency compared to other major metropolitan areas with similar conditions. In the V-super efficiency results of the efficiency model based on the input of operational costs for each new mode of transportation, considering variable returns to scale (VRS), the bus rapid transit (BRT) ranked first, the tramway second, and the bimodal tram third. Regarding construction cost input, the tramway ranked first, the bimodal tram second, and BRT third.
The global averaged civilian positioning accuracy is still at meter level for all existing Global Navigation Satellite Systems (GNSSs), and the performance is even worse in urban areas. At lower altitudes than satellites, high altitude platform stations (HAPS) offer several benefits, such as lower latency, less pathloss, and likely smaller overall estimation error for the parameters associated in the pseudorange equation. HAPS can support GNSSs in many ways, and in this paper we treat the HAPS as another type of ranging source. In so doing, we examine the positioning performance of a HAPS-aided GPS system in an urban area using both a simulation and physical experiment. The HAPS measurements are unavailable today; therefore, they are modeled in a rather simple but logical manner in both the simulation and physical experiment. We show that the HAPS can improve the horizontal dilution of precision (HDOP), the vertical dilution of precision (VDOP), and the 3D positioning accuracy of GPS in both suburban and dense urban areas. We also demonstrate the applicability of a RAIM algorithm for the HAPS-aided GPS system, especially in the dense urban area.
Cancer is a significant health issue globally and it is well known that cancer risk varies geographically. However in many countries there are no small area level data on cancer risk factors with high resolution and complete reach, which hinders the development of targeted prevention strategies. Using Australia as a case study, the 2017-2018 National Health Survey was used to generate prevalence estimates for 2221 small areas across Australia for eight cancer risk factor measures covering smoking, alcohol, physical activity, diet and weight. Utilising a recently developed Bayesian two-stage small area estimation methodology, the model incorporated survey-only covariates, spatial smoothing and hierarchical modelling techniques, along with a vast array of small area level auxiliary data, including census, remoteness, and socioeconomic data. The models borrowed strength from previously published cancer risk estimates provided by the Social Health Atlases of Australia. Estimates were internally and externally validated. We illustrated that in 2017-18 health behaviours across Australia exhibited more spatial disparities than previously realised by improving the reach and resolution of formerly published cancer risk factors. The derived estimates reveal higher prevalence of unhealthy behaviours in more remote areas, and areas of lower socioeconomic status; a trend that aligns well with previous work. Our study addresses the gaps in small area level cancer risk factor estimates in Australia. The new estimates provide improved spatial resolution and reach and will enable more targeted cancer prevention strategies at the small area level, supporting policy makers, researchers, and the general public in understanding the spatial distribution of cancer risk factors in Australia. To help disseminate the results of this work, they will be made available in the Australian Cancer Atlas 2.0.
Rhanda Kyerewaa Opuni, Dina Adei, Anthony Acquah Mensah
et al.
Abstract Background In low-and middle-income countries, migrants are confronted with health needs which affect the promotion of their well-being and healthy lives. However, not much is known about the health needs of migrant female head porters (Kayayei) in Ghana. This study assesses the health needs of migrant female head porters in the Greater Kumasi Metropolitan Area (GKMA) and Greater Accra Metropolitan Area (GAMA). Methods The study adopted a convergent mixed methods design where both qualitative and quantitative data were used. A representative sample size of 470 migrant female head porters was used for the study. Results The study revealed that ante-natal care, post-natal care, treatment of malaria, treatment of diarrhoea diseases, mental health, sexual health, and cervical cancer were health needs of migrant female head porters. The findings showed that participants from the GAMA significantly have greater cervical cancer needs (71.6% vrs 67.1%, p = 0.001) compared to those from the GKMA. Kayeyei from the GKMA significantly have greater mental health needs than those from the GAMA (84.6% vrs 79.2%, p = 0.031). Also, Kayeyei from the GKMA significantly have higher attendance of post-natal care compared to those from the GAMA (99.4% vrs 96.2%, p = 0.013). Conclusion The findings underscore differential health needs across geographical localities. Based on the findings of the study, specific health needs such as ante-natal care and post-natal care should be included in any health programmes and policies that aim at addressing health needs of migrant female head porters in the two metropolitan areas of Ghana.
In this paper, new methods are considered to detect knee joint areas in bilateral PA fixed flexion knee X-ray images. The methods are of template matching type where the distance criterion is based on the negative normalized cross-correlation. The manual annotations are made on only one side of a single bilateral image when the templates are selected. The best matching patch search is formulated as an unconstrained continuous domain minimization problem. For the minimization problem different optimization methods are considered. The main method of the paper is a trainable optimizer where the method is taught to take zoomed and possibly rotated patches from its input images which look like the template. In the experiments, we compare the minimum values found by different optimization methods. We also look at some test images to examine the correspondence between the minimum value and how well the knee area is localized. It seems that making annotations only to a single image enables to detect knee joint areas quite precisely.
A well-developed perspective in the study of urban systems is that cities are complex systems that manifest as networks of interdependent economic units. These units might be occupations, industries, labor skills, patent technologies, etc. Much research has focused on describing the nature of these networks, quantifying their links, and suggesting applications for policymakers. In this paper, we examine the US skill network, focusing on the relationship between network centrality and economic performance. Here, nodes are represented by individual labor skills, and edge weights are derived from the colocation pattern of skill pairs among 384 US metropolitan statistical areas. The centrality of skills, using three centrality measures, is then aggregated to the occupational and metropolitan level. We find that occupations with higher skill centrality are associated with greater annual salaries, and metropolitan areas with higher skill centrality have higher productivity rates. Overall, these results suggest that the application of traditional network metrics to this view of cities as complex networks can offer new insights into the dynamics of regional economies.
Global warming is causing increasing Heat Waves that affect human health. High temperatures markedly increase morbidity and mortality. Urban Heat Islands increase the effects of Heat Waves and are a serious inconvenience to human health and comfort. Cities can substantially increase local temperatures and reduce temperature drop at night. During the night, the greater thermal inertia of the central areas reduces their cooling capacity. On the other hand, it is important to highlight that urban vegetation plays a key role in adapting cities to Global Warming and Urban Heat Island. Green areas have lower temperatures than the rest of land uses and generate a cooling effect that spreads to their surroundings creating a "cool island" effect. The main objective of this paper is to establish the nocturnal land surface temperature and land surface air temperature of Barcelona Metropolitan Area (35 municipalities, 636 km<sup>2</sup>, 3.3 million inhabitants) in an episode of a nocturnal heatwave and to estimate its possible impact on health and mortality. Subsequently, nighttime temperatures are analysed in this extreme heat context to determine their spatial distribution and detect the urban landscapes that are most vulnerable to extreme night heat. Modelling of land surface temperature must reveal the elements that determine night Urban Heat Island and consequently identify actions that can be implemented at urban planning level to refresh the environment during the night and thus increase the resilience of the most vulnerable landscapes and improve residents’ health. This paper studies the effect of urban greenery and green infrastructures on Nighttime Urban Heat Island and propose climate adaptation measures and design for urban green areas to decrease high temperature in a Heat Wave context, which contributes to reducing the serious negative impacts on people's health.
Despite the proliferation of mobile devices in various wide-area Internet of Things applications (e.g., smart city, smart farming), current Low-Power Wide-Area Networks (LPWANs) are not designed to effectively support mobile nodes. In this paper, we propose to handle mobility in SNOW (Sensor Network Over White spaces), an LPWAN that operates in the TV white spaces. SNOW supports massive concurrent communication between a base station (BS) and numerous low-power nodes through a distributed implementation of OFDM. In SNOW, inter-carrier interference (ICI) is more pronounced under mobility due to its OFDM based design. Geospatial variation of white spaces also raises challenges in both intra- and inter-network mobility as the low-power nodes are not equipped to determine white spaces. To handle mobility impacts on ICI, we propose a dynamic carrier frequency offset estimation and compensation technique which takes into account Doppler shifts without requiring to know the speed of the nodes. We also propose to circumvent the mobility impacts on geospatial variation of white space through a mobility-aware spectrum assignment to nodes. To enable mobility of the nodes across different SNOWs, we propose an efficient handoff management through a fast and energy-efficient BS discovery and quick association with the BS by combining time and frequency domain energy-sensing. Experiments through SNOW deployments in a large metropolitan city and indoors show that our proposed approaches enable mobility across multiple different SNOWs and provide robustness in terms of reliability, latency, and energy consumption under mobility.
Kifah Al-Maqrashi, Fatma Al-Musalhi, Ibrahim M. Elmojtaba
et al.
A mathematical model of Zika virus transmission incorporating human movement between rural areas and nearby forests is presented to investigate the role of human movement in the spread of Zika virus infections in human and mosquito populations. Proportions of both susceptible and infected humans living in rural areas are assumed to move to nearby forest areas. Direct, indirect and vertical transmission routes are incorporated for all populations. Mathematical analysis of the proposed model has been presented. The analysis starts with normalizing the proposed model. Positivity and boundedness of solutions to the normalized model have been then addressed. The basic reproduction number has been calculated using the next generation matrix method and its relation to the three routes of disease transmission has been presented. The sensitivity analysis of the basic reproduction number to all model parameters has been investigated. The analysis also includes existence and stability of disease free and endemic equilibrium points. Bifurcation analysis has been also carried out. Finally, numerical solutions to the normalized model have been obtained to confirm the theoretical results and to demonstrate the impact of human movement in the disease transmission in human and mosquito populations.