Search Results (22)

This study presents a comparative analysis of residential segregation among the three largest foreign-born populations residing in Spain: Moroccans, Romanians, and Colombians. Using data from Spain’s Population and Housing Census (INE), the research analyzed the segregation index across 34 urban areas in medium-sized cities. Three urban areas in Catalonia were selected for the intraurban case studies, and Pearson correlation coefficients were calculated for 60 sociodemographic variables. The objectives were to identify indicators that helped diagnose potential segregation contexts and to explore residential patterns by country of origin. The study was grounded in a central premise: the foreign-born population cannot be treated as a homogeneous group, as aggregation conceals group-specific inequalities and differentiated spatial configurations. The findings showed that segregation occurred. Moroccans exhibited the highest levels of segregation, which was associated with socioeconomic vulnerability and also a marked residential preference for central urban areas. Colombians displayed lower levels of segregation and greater territorial dispersion, pointing to broader residential access. Romanians presented intermediate and heterogeneous patterns, which combined localized concentrations with peripheral settlement. The results highlighted how intraurban differentiation emerged from interactions between different migrant profiles, housing opportunity structures, and urban morphology, providing an empirical basis on which to design targeted urban policies. Full article

To explore the variation in leaf phenotypic traits and environmental adaptation strategies of Pinus densata in southeastern Xizang, 15 plots were established across five regions—Gongbujiangda County (GB), Bomi County (BM), Bayi District (BY), Milin City (ML), and Lang County (LX)—and 11 leaf traits were measured, including leaf length (LL), width (LD), area (LA), volume (LV), fresh weight (LFW), dry weight (LDW), tissue density (LTD), specific leaf area (SLA), and leaf greenness index (SPAD). Results showed that all traits except LL varied significantly among regions, with moderate variation overall; SPAD exhibited the highest coefficient of variation, while leaf water content was the most stable. Extensive correlations were detected among traits: leaf size and weight traits were positively intercorrelated and all negatively correlated with LTD, and SLA correlated negatively with LTD but positively with SPAD. Principal component analysis and hierarchical clustering further revealed that phenotypic variation aligned with the leaf economic spectrum and grouped the populations into three strategy types. Specifically, GB populations approached the “slow investment–return” end of the spectrum, BY and BM populations the “fast investment–return” end, while ML and LX occupied intermediate positions (transitional strategies), with ML leaning toward the slow end. These findings demonstrate that P. densata in southeastern Xizang has evolved diverse resource use and adaptation strategies through synergistic and trade-off relationships among leaf traits, enabling its persistence in complex high-altitude environments. Full article

The management of municipal solid waste in intermediate cities exhibits high daily variability and source heterogeneity, which hinders operational sizing and material recovery. Reliable predictions are required from heterogeneous and often-scarce data. However, studies that compare multiple machine learning algorithms with temporal validation on short time series in intermediate cities are still limited. This study compares fourteen machine learning algorithms to predict the daily generation of organic and inorganic waste in La Joya de los Sachas, Ecuador, formulating the problem as a multi-output regression problem. An adapted CRISP-DM design was employed, using primary data from a waste characterization campaign, temporal feature engineering, variable encoding, and an expanding-window backtesting protocol against lag-7 persistence and ARIMA. Tree-based ensembles achieved the best performance. AdaBoost provided the best organic forecasts ($R^2$$=0.985$, $\mathrm{RMSE}$ $=0.081$, $\mathrm{MAE}$$=0.061$ in rate space), while Random Forest was best for inorganic ($R^2$$=0.965$, $\mathrm{RMSE}$ $=0.049$, $\mathrm{MAE}$$=0.040$). Linear models were stable but slightly inferior, and other approaches (SVR, KNN, MLP, Lasso, ElasticNet) showed lower generalization capacity. The study provides a multi-output regression protocol with temporal validation for municipal contexts with short time series, comparative evidence across fourteen algorithms, and a conversion from rates to kilograms for operational use. Full article

This research is focused on housing stock rehabilitation and construction in Urban Rehabilitation Areas located in diverse contexts in the Portuguese territory. The main objective of this research is to show how the local actors have managed the ARUs’ opportunities to restore and develop the housing in these areas in the Portuguese territory. An analytical national legal framework is made to show that the diffuse criteria at national and regional levels are reflected in the limited effectiveness of the ARUs’ flexible criteria in local implementation. A national legislative and regulatory framework in Portugal, focusing on urban rehabilitation and housing promotion themes, is discussed to emphasize the potential role of Urban Rehabilitation Area (ARU) particularities and housing provision and preservation in diverse contexts in Portugal. A comparative analysis is conducted of five ARUs—Belmonte, Soure, Penacova, Vila Real, and Devesas—located in Portugal, in the North and Center regions, to highlight the particularities/diversity of urban contexts, including towns, small to medium-sized cities, and historic centres. The analysis assesses the effectiveness of ARU urban rehabilitation strategy implementation over time. The analysis of five ARUs will discuss the following: (i) ARU physical characteristics; (ii) ARU population profile; (iii) ARU urban rehabilitation strategies progress (initial, intermediate, and final); and (iv) ARU alignment with PDM priorities in urban rehabilitation. The findings underscore the pivotal role that ARUs and their actors can have in housing rehabilitation provision and preservation on different scales and contexts within the territory. The outcomes show different strategies that each ARU has used to prioritize building rehabilitation. Full article

There is an urgent need for a thorough assessment of forest landscape fragmentation to inform forest protection and restoration, and reforestation policies. However, there is currently a lack of an effective comprehensive index for forest landscape fragmentation, and detailed knowledge of the forest landscape fragmentation dynamics remains insufficient. Here, taking Putian City of Fujian Province in Southeastern China as a case, we employed a forest fragmentation comprehensive index (FFCI) to capture key features of forest landscape fragmentation, such as patch size, number, and distribution. Then, bivariate spatial autocorrelation analysis was employed to identify the spatial associations between the static forest landscape fragmentation (FFCI) and the dynamic forest landscape fragmentation (ΔFFCI), and the spatial coupling modes among the three individual components of FFCI (mean patch area, MPA; aggregation index, AI; patch density, PD) were identified to explore the detail process of forest landscape fragmentation. Finally, the random forest model was applied to observe the impact factors of forest landscape fragmentation dynamics. The findings showed that forest landscapes with different degrees of fragmentation exhibited more noticeable changes at both ends (i.e., either high or lower-level fragmentation), with the intermediate level remaining consistent from 2000 to 2020. Around 18.3% of forest landscapes experienced a decrease in fragmentation, particularly in the northern part of the study area, while approximately 81.7% of forest landscapes exhibited an increasing trend in fragmentation. The bivariate spatial autocorrelation analysis indicated that the proportion of Low–High-type grids was the highest at 17.3%, followed by the High–High type at 7.0%. We also identified eight forest landscape fragmentation modes, which indicate the most significant forest landscape fragmentation pattern is a decrease in MPA and an increase in PD. Moreover, the anthropogenic factors (e.g., population density and night light intensity) were found to dominate the FFCI dynamics during 2000–2020. This study offers an efficient research paradigm for the dynamics of forest landscape fragmentation. The outcomes are conducive to an in-depth comprehension of the detailed dynamic information of forest landscape fragmentation, and supply a scientific foundation for enhancing the overall ecological service function of the forest. Full article

International shipping’s particulate matter primary emissions have a share in global anthropogenic emissions of between 3% and 4%. Ship emissions of volatile organic compounds (VOCs) can play an important role in the formation of fine particulate matter. Using an aerosol box model for the near-plume scale, this study investigated how the changing VOC emission factor (EF) for ship engines impacts the formation of secondary PM_2.5 in ship exhaust plumes that were detected during a measurement campaign. The agreement between measured and modeled particle number size distribution was improved by adjusting VOC emissions, in particular of intermediate-, low-, and extremely low-volatility compounds. The scaling of the VOC emission factor showed that the initial emission factor, based on literature data, had to be multiplied by 3.6 for all VOCs. Information obtained from the box model was integrated into a regional-scale chemistry transport model (CTM) to study the influence of changed VOC ship emissions over the Mediterranean Sea. The regional-scale CTM run with adjusted ship emissions indicated a change in PM_2.5 of up to 5% at the main shipping routes and harbor cities in summer. Nevertheless, overall changes due to a change in the VOC EF were rather small, indicating that the size of grid cells in CTMs leads to a fast dilution. Full article

Throughout the 20th century and in the first decades of the 21st century, the geospatial dynamic exhibiting the highest rate of change globally corresponds to urban expansion surrounding metropolitan areas and large cities. Around intermediate-sized cities, there have also been rapid changes in their geographical space, but study in these areas has had less academic attention and development. Considering this context, this article intends to analyze the dynamics in the periurbanization of communes with intermediate-sized cities. In this study, three geographical criteria were defined for the definition of the study area and seven geospatial indicators of sociodemographic, socioeconomic and land occupation categories, with the purpose of determining the composition of the periurbanization process. Finally, the discussion presents a perspective on the dynamics of periurbanization, the interpretation of future projections identifying three geospatial phenomena and a proposal for a geospatial chorematic model with the composition of periurbanization, based on three subregional intermediate-sized cities in the Metropolitan Region of Santiago de Chile. This research contributes new reflections to the debate around spatial planning and periurban research in Latin America and the Global South. Full article

Thelazia callipaeda is a zoonotic parasitic nematode that lives in the ocular conjunctival sac of domestic and wild carnivores, lagomorphs, and humans, with Phortica spp. as its intermediate host. At present, the important role that domestic dogs play in thelaziosis has been studied in many countries. However, Beijing, which is the first city in China to experience human thelaziosis, has not yet conducted a comprehensive epidemiological analysis of the disease. In this study, we analyzed risk factors (region, season, age, sex, breed, size, living environment, diet, country park travel history, immunization history, anthelmintic treatment history, and ocular clinical symptoms) associated with the prevalence of thelaziosis in domestic dogs in Beijing. The overall prevalence of T. callipaeda in the study area was 3.17% (102/3215 domestic dogs; 95% CI 2.57–3.78%). The results of the risk factor analysis showed that thelaziosis in domestic dogs from Beijing was significantly correlated with regional distribution, seasonal distribution, country park travel history, and anthelmintic treatment history (p < 0.05). In summer and autumn, domestic dogs living in mountainous areas, with a history of country park travel and without deworming were 4.164, 2.382, and 1.438 times more infected with T. callipaeda than those living in plain areas without a history of country park travel and with a history of deworming (OR = 4.164, OR = 2.382, OR = 1.438, respectively). T. callipaeda-infected domestic dogs did not always show any ocular clinical symptoms, while symptomatic domestic dogs were mainly characterized by moderate symptoms. The results indicate that in summer and autumn, preventive anthelmintic treatment should be strengthened for domestic dogs with a country park travel history or those living in mountain areas. At the same time, we should be vigilant about taking domestic dogs to play in country parks or mountainous areas during summer and autumn because this may pose a potential risk of the owner being infected with T. callipaeda. Full article

Digitalization in water networks is essential for the future planning of urban development processes in cities and is one of the great challenges faced by small cities regarding water management and the advancement of their infrastructures towards sustainable systems. The main objective of this study is to propose a methodology that allows water utilities with limited budgets to start the path toward the digitalization and construction of the hydraulic model of their water distribution networks. The small city of Pamplona in Colombia was used as a case study. The work explains in detail the challenges faced and the solutions proposed during the digitalization process. The methodology is developed in six phases: an analysis of the cadastre and existing information, the creation and conceptualization of the base hydraulic model, the development of the topography using drones with a limited budget, an analysis of water demand, the development of a digital hydraulic model, and a hydraulic analysis of the system. The product generated is a tool to assess the overall performance of the network and contributes to the advancement of SDG-6, SDG-9, and SDG-11. Finally, this document can be replicated by other cities and companies with similar characteristics (e.g., limited size and budget) and offers an intermediate position on the road to digitalization and the first steps towards the implementation of a digital twin. Full article

Element flow has gradually become an important method for studying urban spatial structure. This study examined 11 prefectural cities in the Guanzhong Plain urban agglomeration; constructed a measurement model for information, traffic, migration, and composite networks; and analyzed the spatial structure of the urban network of the urban agglomeration through social network analysis and spatial visualization. The spatial structure of the composite flow network had Xi’an as the center and Xianyang, Baoji, Weinan and Tianshui as important nodes; Yuncheng, Linfen and Qingyang were the secondary nodes, radiating to the surrounding three cities. Element flow connection strength was unbalanced, and only three city pairs were in the first level of the composite flow network. Network density was low-middle, and the network connection was weak. Xi’an was the primary central city of the Guanzhong Plain urban agglomeration with the strongest agglomeration and radiation capabilities; it could communicate with other cities without intermediate cities and was a bridge for other cities. Tongchuan, Pingliang, Shangluo, and Qingyang were at the edge of the urban agglomeration and had weak agglomeration, radiation, and intermediary capabilities. The inner cities of cohesive subgroups were closely related with weak connections between subgroups. The single-polarization of the Guanzhong Plain urban agglomeration was serious, and the single-core spatial structure centered on Xi’an had limited impact on the urban agglomeration. Development of small and medium-sized cities should be strengthened in the future. Full article

Based on the data from 35 major cities in China in 2020, this paper applies the Simpson’s diversity index, the entropy value method, and the coupling coordination degree model to comprehensively measure the coupling coordination level of mixed land use and urban vitality in major cities in China and further analyze their spatial distribution characteristics. In addition, this paper analyzes the factors affecting the spatial variation of the coupling coordination level with the help of the geographic probe model. The study finds that: (1) The overall level of coupling coordination between mixed land use and urban vitality is high in 35 major cities in China. There is no disorder between mixed land use and urban vitality. (2) In terms of the spatial distribution of the coupling coordination between mixed land use and urban vitality in 35 cities in China, five cities, namely Beijing, Shenzhen, Shanghai, Guangzhou, and Chengdu, have the highest level of coupling coordination between mixed land use and urban vitality, reaching “good coordination” with a discrete spatial distribution. Central cities such as Hangzhou and Nanjing have the second highest level of coupling coordination and are at the “intermediate coordinate” with a “strip-like distribution” in space. Twenty cities in the north and south have the lowest coupling coordination levels and are in the “primary coordination.” Among these twenty cities, seven cities in the south have a higher level of coupling coordination than thirteen cities in the north, with a spatial distribution of a “C” shape. The northern cities have the lowest level of coupling coordination, with a “W”-shaped distribution in space. (3) Population size plays an essential role in guiding the level of coupling coordination between mixed land use and urban vitality in major cities in China, followed by government regulation and economic level. At the same time, transportation conditions and industrial structure have the weakest influence on the level of coupling coordination between mixed land use and urban vitality in major cities in China. Full article

This study develops a data-driven, comprehensive evaluation method to improve the science and technology innovative efficiency of industrial enterprises above designated size (hereinafter “industrial enterprises”). Based on an innovation value chain perspective, a two-stage evaluation index system is constructed. Thereafter, the Pearson correlation coefficient method was used to analyze correlations in the constructed index system. A two-stage network data envelopment analysis model with additional intermediate input was constructed to measure and evaluate industrial enterprises’ science and technology innovative efficiency from three aspects—research and development (R&D), commercialization, and comprehensive efficiencies—to reveal the temporal and spatial evolution. The feasibility and effectiveness of the method was verified using the statistical data of industrial enterprises in 16 cities in Anhui Province, China, from 2011 to 2020. The results show that the comprehensive efficiency of the scientific and technological innovation of industrial enterprises in these cities is at a medium level, and the efficiency development of the two stages is uncoordinated; the two-stage efficiency distribution tends to be “high R&D–high commercialization” and “low R&D–low commercialization”, and targeted countermeasures and suggestions are proffered. This study provides a reference for the sustainable development of industrial enterprises in relevant regions. Full article

Compact development and efficient land use are effective ways to address the development dilemma and boost the vitality of shrinking cities. Moreover, it is critical to investigate the relationship between compactness and land-use efficiency in order to healthily and sustainably develop shrinking cities. This study developed an analytical framework to study the coordinated interaction between urban compactness and land-use efficiency in the context of city shrinkage. Fifteen typical shrinking cities in Northeast China were taken as an example of the phenomenon and the entropy value method and super-slack-based measure model were used to quantitatively measure the compactness and land-use efficiency. Furthermore, the coordinated development level and the coordinated relationship between the two were explored with the help of the coupled coordination degree model as well as the quadrant diagram method. The results of the study show that: (1) The overall level of compactness of 15 shrinking cities in Northeast China was low and the improvement of land-use efficiency was not obvious, while the differences of compactness and land-use efficiency between shrinking cities were significant. (2) The coordination between compactness and land-use efficiency was limited; however, the overall coordination remained intermediate, with significant spatial differences and a tendency to further expand. The problem of lagged development of land-use efficiency in shrinking cities could be characterized as serious. (3) Economic development and population size promote the coordinated development of urban compactness and land-use efficiency, whereas science and technology development, industrial structure, as well as government regulation inhibited the coordinated development of urban compactness and land-use efficiency. Full article

In the field of building detection research, an accurate, state-of-the-art semantic segmentation model must be constructed to classify each pixel of the image, which has an important reference value for the statistical work of a building area. Recent research efforts have been devoted to semantic segmentation using deep learning approaches, which can be further divided into two aspects. In this paper, we propose a single-side dual-branch network (SSDBN) based on an encoder–decoder structure, where an improved Res2Net model is used at the encoder stage to extract the basic feature information of prepared images while a dual-branch module is deployed at the decoder stage. An intermediate framework was designed using a new feature information fusion methods to capture more semantic information in a small area. The dual-branch decoding module contains a deconvolution branch and a feature enhancement branch, which are responsible for capturing multi-scale information and enhancing high-level semantic details, respectively. All experiments were conducted using the Massachusetts Buildings Dataset and WHU Satellite Dataset I (global cities). The proposed model showed better performance than other recent approaches, achieving an F1-score of 87.69% and an IoU of 75.83% with a low network size volume (5.11 M), internal parameters (19.8 MB), and GFLOPs (22.54), on the Massachusetts Buildings Dataset. Full article

Introduction: Various drug–food interactions exist that may hinder treatment and can sometimes be lethal. Our aim was to assess the level of public knowledge and awareness in Jeddah city, Western Saudi Arabia, about drug–food interactions, along with the effects of demographics on their knowledge. Methods: A survey questionnaire was administered in this cross-sectional study to participants spread across multiple locations in Jeddah, including in malls and public gatherings. Participants included both males and females. Sample size was calculated through Raosoft^® software. Data analysis was executed using IBM Statistic SPSS and the level of statistical significance was set at p < 0.05. Results: A total of 410 people participated in the study and only 92.68% (380) of responses were enrolled in the study; 7.32% (30) were not enrolled due to the exclusion criteria. Surprisingly, only six out of eighteen questions regarding drug–food interactions in the administered questionnaire were correctly answered by 380 participants. Data indicated that the participants had a poor to intermediate level of both knowledge and awareness with respect to drug–food interactions. Furthermore, participants showed moderate to strong awareness of the effects of alcohol and tea generally, and their interaction with medication. Conclusion: Participants in our study showed inadequate knowledge of basic and fundamental information about drug–food interactions, which highlights the dire need to increase awareness. Full article