Search Results (58)

According to statistics, between 1954 and 2021, China experienced 3558 dam failures in reservoirs, with flood overtopping accounting for 51.04% of these incidents. Once an earth-rock dam fails, it not only directly threatens the lives and property of surrounding residents and disrupts normal living order, but also damages infrastructure such as farmland, transportation, and power systems, resulting in enormous economic losses. To investigate the mechanisms of overtopping failure and breach evolution in homogeneous earthen embankments during flood seasons, this study conducted seven sets of laboratory model tests with the Changkai Embankment in Fuzhou City, Jiangxi Province, as a prototype. The tests considered various operational conditions, including different crest widths, embankment heights, channel water depths, and river flow velocities. The test results are as follows: Overtopping failure of earth embankments can be categorised into three distinct stages. The breach formation process can be categorised into three stages: vertical erosion (stage I), breach expansion (stage II) and breach stabilisation (stage III). River water levels and inflow rates were identified as pivotal factors influencing the final morphology of the breach and the flow velocity within it. Conversely, the height of the dike was found to have little influence on the shape of the breach and the flow velocity. The breach width ranges from 6 cm to 12 cm. An increase in water depth, corresponding to a greater difference in water levels on both sides of the river, has been observed to result in a deeper breach and faster widening rate. Elevated water levels have been shown to increase the potential energy of the water, which is subsequently converted into greater kinetic energy during breach formation. This, in turn, increases the flow velocity at the breach. However, a negative correlation has been observed between inflow velocity and flow at the breach. This paper combines the material properties of the embankment to discuss the overtopping failure mechanism and the breach evolution law of homogeneous earth embankments. This provides a basis for preventing and controlling embankment failure disasters. Full article

A major challenge that will confront our society in the coming years is the socioecological transition. This involves a profound, systemic shift in how human societies interact with ecological systems. Beyond merely becoming “greener” or adding new technologies, it is about reorganising economies, lifestyles, institutions and cultural values to align with the planet’s ecological limits. The change also requires transforming the fundamental structure of societies to ensure their deep interconnection and compatibility with natural flows and ecological systems. To this end, it is valuable to explore the small, scattered practices which are currently leading to new organisational solutions or socioecological improvements. These initiatives are often regarded as forms of community resistance, adopting various approaches and strategies, which result in a disparate array of configurations. A comprehensive approach is thus needed to identify common patterns of development. A set of meaningful practices was analysed. The sample actions all took place in the urban context of Seville, a city located in Southwestern Europe and spanned various arenas driven by the transition to sustainability. Following the principles of qualitative research and a case study design, we adopted a qualitative method based on open-ended interviews, emphasising situated knowledge and collective construction of meaning. Moreover, a methodological approach based on interviews and further categorisation was followed to describe and organise ideas, motivations, risks, outcomes, as well as how the experiences evolved. The findings revealed that the core motivation driving the initiative in its initial phases is key. Outcomes nevertheless vary significantly depending on the initiative objectives. Generally, actions focused on specific elements—such as defending precise locations or activities—tend to be more successful and abundant. But the ones based on professional developments end up being somewhat stifled since they depend on the market to succeed. However, most rely somehow on public subsidies or support from public institutions, and their activities tend to diminish when such resources are reduced or withdrawn. The question is therefore how to make these initiatives more resilient in the future. The socioecological transition offers a path to strengthen social cohesion, empower collective action, and generate locally rooted and ecologically sustainable alternatives. Building community resilience—the capacity of local communities to adapt, recover and thrive amid these challenges—is, therefore, essential. Full article

Digital technology transfer plays a pivotal role in reshaping innovation landscapes and fueling the growth of the digital economy. To investigate this phenomenon, this study draws on data on digital technology transfers from the China National Intellectual Property Administration (CNIPA). Using tools such as Gephi 0.10.1 and ArcGIS 10.8, we construct an inter-city digital technology transfer network and develop a quantitative model to analyse the mechanisms by which it impacts urban digital innovation across multiple geographic scales. The main findings are as follows: (1) The inter-city digital technology transfer network in China forms a “diamond-shaped” spatial structure centred on Beijing, Shanghai, Guangzhou, and Shenzhen, with several regional hubs sustaining its connectivity and organisation. (2) Despite a decline in the proportion of intra-city transfers, the number of participating cities continues to rise, revealing a spatial pattern of diffusion from core cities toward inland provincial capitals. (3) Benchmark regression results show that both inter- and intra-city transfers significantly enhance urban digital innovation capacity, with inter-city transfers exhibiting a more substantial effect than their intra-city counterparts. This finding holds after a series of robustness tests. (4) Heterogeneity analysis, based on categorising cities into higher-tier (municipalities, sub-provincial cities, and provincial capitals) and lower-tier groups, indicates that the effect of digital technology transfer on innovation is more pronounced in lower-tier cities. Full article

Background and Objectives: To evaluate the prognostic value of the Clinical–Pathologic Stage–Estrogen receptor status and Grade (CPS+EG) staging system, which combines clinical staging, pathological staging, oestrogen receptor (ER) status, and tumour grade in predicting survival outcomes in patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer receiving neoadjuvant therapy (NACT). Materials and Methods: A retrospective review was performed on 245 female breast cancer patients who received anti-HER2 therapy alongside NACT at the Medical Oncology Department of Kartal Dr Lütfi Kırdar City Hospital, University of Health Sciences, from April 2012 to June 2024. The CPS+EG score was calculated using the MD Anderson Cancer Centre neoadjuvant treatment response calculator. Patients were categorised into two groups based on their CPS+EG score < 3 and ≥3. The primary outcomes assessed were disease-free survival (DFS) and overall survival (OS). Kaplan–Meier and log-rank tests were utilised for time-to-event analysis; Cox regression was used for multivariate analysis. A significance level of ≤0.05 was considered. Results: The median age of the patient cohort was 51 years (range: 27–82 years). Among these patients, 183 (74.6%) had a CPS+EG score less than 3, while 62 (25.3%) exhibited a score of 3 or higher. The median follow-up duration was 37.6 months. The pathological complete response (pCR) rate across the entire cohort was 51.8%. Specifically, the pCR rate was 56.3% in the group with CPS+EG scores below 3, and 38.7% in those with scores of 3 or higher (p = 0.017). Patients with CPS+EG scores less than 3 demonstrated superior overall survival (OS), which reached statistical significance in univariate analysis. Multivariate analysis identified the CPS+EG score as an independent prognostic factor for both overall survival and disease-free survival (DFS), with hazard ratios of 0.048 (95% CI: 0.004–0.577, p = 0.017) and 0.35 (95% CI: 0.14–0.86, p = 0.023), respectively. Conclusions: The CPS+EG score is an independent and practical prognostic marker, particularly for overall survival, in patients with HER2-positive breast cancer who have received neoadjuvant therapy. Patients with a CPS+EG score < 3 have higher pCR rates and survival rates. When used in conjunction with pCR, it can improve risk categorisation and contribute to the individualisation of adjuvant strategies in the post-neoadjuvant period. Due to its ease of calculation and lack of additional costs, this score can be instrumental in clinical practice for identifying high-risk patients. Our findings support the integration of the CPS+EG score into routine clinical decision-making processes, although prospective validation studies are necessary. Full article

Air quality significantly affects human health, productivity, and overall well-being. This study applies machine learning techniques to analyse and predict air quality in Hamilton, New Zealand, focusing on particulate matter (PM2.5 and PM10) and environmental factors such as temperature, humidity, wind speed, and wind direction. Data were collected from two monitoring sites (Claudelands and Rotokauri) to explore relationships between variables and evaluate the performance of different predictive models. First, the unsupervised k-means clustering algorithm was used to categorise air quality levels based on data from one or both locations. These cluster labels were then used as target variables in supervised learning models, including random forests, decision trees, support vector machines, and k-nearest neighbours. Model performance was assessed by comparing prediction accuracy for air quality at either Claudelands or Rotokauri. Results show that the random forest (93.6%) and decision tree (91.8%) models outperformed k-nearest neighbours (KNN, 83%) and support vector machine (SVM, 61%) in predicting air quality clusters derived from k-means analysis. The three clusters (very good, good, and moderate) reflected seasonal and urban–semi-urban gradients, while cross-location validation confirmed that models trained at Claudelands generalised effectively to Rotokauri, demonstrating scalability for regional air quality forecasting. These findings highlight the potential of combining clustering with supervised learning to improve air quality predictions. Such methods could support environmental monitoring and inform strategies for mitigating pollution-related health risks in New Zealand cities and beyond. Full article

The urbanisation process of cities disrupts the natural energy balance and surface radiation, making cities relatively warm. While vegetation has been widely recognised as a key factor in mitigating urban heat, its effectiveness is shaped by interactions with urban morphology, surface cover types, and the background climate. This paper presents a bibliometric analysis of studies examining the role of vegetation in mitigating urban heat, with a particular focus on its interactions within the urban environment across four major Köppen–Geiger climate groups: tropical, arid, temperate, and cold. A total of 130 publications were reviewed, categorised, and analysed according to geographic distribution, study period, and methodological approaches. This review identifies underexplored areas, synthesises key findings, and summarises the most significant results. Vegetation and water bodies emerged as primary contributors to heat mitigation, along with building configuration, wind speed, and shading. Temperate climates were the most frequently studied. Remote sensing was the predominant methodological approach, followed by fixed in situ observations. Meso-scale studies, examining entire cities and their surroundings, dominated in terms of spatial scale. This review offers methodological recommendations for analysing urban vegetation within the context of urban climate research. As climate change intensifies, it is increasingly important to design and implement adaptation strategies that incorporate but are not limited to vegetation. Such strategies are essential to supporting sustainable and resilient urban development in diverse climatic contexts. Full article

Against the background of traffic conflicts arising due to the highly concentrated population in high-density cities, this study aims to systematically identify the core transport needs of patients awaiting medical treatment; based on the theory of the Kano model, we construct a measurement system relating to patient transport needs when awaiting medical treatment that encompasses multiple levels. Taking 10 large general hospitals in Guangzhou as samples, this study collected data through questionnaires and auxiliary interviews, using the importance–sensitivity analysis method to accurately measure the degree of patient needs for each influencing factor of the transport environment for medical treatment. The study found that, among the primary needs (core basic needs), the perfection of public transport (which directly affects the convenience of medical care) is the core need with the highest degree of demand. Among the second-level needs (refined categorised demand levels), specifically relating to important attributes (essential needs), priority attention should be given to patient diversion, hospital–city connection, and corridor settings. As concerns the high value-added one-dimensional attributes (desired needs), focus should be placed on controlling health and safety distances and guiding the flow of medical treatment, while for high glamour attributes (glamour needs), primary consideration should be given to crowd distribution, stopping and resting, and direct access to the ground floor. The group difference analysis (grouped by emotional state, transport mode, and group type) showed that the first-level demand sensitivity ranking was highly consistent, and the second-level demand for urban connectivity, convenient transfer, and direct underground access were also common priorities. This study is the first to introduce the Kano model into the analysis of high-density urban healthcare transport systems, providing a clear basis for the grading of demand for the design of the transport environment for patients’ medical care. This is of great practical value for alleviating congestion and improving the resilience of emergency response in mega-cities in relation to medical care. Full article

Urban–rural integration realises the coordinated development and prosperity of urban and rural areas as a whole by optimising the allocation of resources and the flow of factors, and its connotations have been extended from a single dimension to multiple dimensions such as people, land and industry. The Beijing–Tianjin–Hebei Region has a typical “Core–Periphery Structure”, and this paper took the 187 county units within the region as the research object, taking into account indicators of development and coordination to construct an evaluation index system of urban–rural integration of the Beijing–Tianjin–Hebei region counties in the dimensions of “people–land–industry”. Global principal component analysis was used to measure the evolutionary pattern of the urban–rural integration level between 2005 and 2020, and its spatiotemporal drivers were analysed by using the Geographical and Temporal Weighted Regression model (GTWR). The results of the study show that (1) the level of urban–rural integration in the Beijing–Tianjin–Hebei region showed an increasing trend during the 15-year study period, the high-value areas of urban–rural integration were mainly distributed in Beijing and the Bohai Rim region in the eastern part of the Tianjin–Hebei region, and the level of urban–rural integration of the peri-urban county units of the city was better than that of the remote counties and cities as a whole. (2) In terms of spatial agglomeration, all dimensions were characterised by significant spatial agglomeration. The degree of agglomeration was categorised as urban–rural comprehensive integration (U-RCI) > urban–rural industry integration (U-RII) > urban–rural land integration (U-RLI) > urban–rural people integration (U-RPI). (3) In terms of spatial and temporal driving factors for urban–rural integration, the driving role of U-RPI, U-RLI and U-RII for U-RCI has gradually weakened during the past 15 years, and urban–rural integration in the counties shifted from a single role to a more central coordinated and multidimensional driving role. Full article

This study examines the identity of nanostores—micro, independent grocery retailers—through a systemic, stakeholder-informed lens to promote their survivability and competitiveness. Moving beyond traditional operational descriptions, it introduces a multidimensional framework that examines what nanostores do (X), how they do it (Y), and why they matter (Z), which is complemented by the use of the TASCOI tool to produce identity statements. Based on survey data collection and a thematic analysis of nanostore stakeholder responses in Mexico City, the research categorises identity statements into six 2 × 2 matrices across four dimensions: operational, functional, relational, and adaptive. This analysis yields twenty-four archetypes that capture the diversity, complexity, and adaptability of nanostores. The findings reveal that nanostores are not a homogeneous category. They simultaneously exhibit characteristics of multiple archetypes, blending retail function, social embeddedness, and entrepreneurial adaptation. This study contributes to the nanostore and micro-enterprise literature by operationalising identity description and offers practical insights for supporting diverse shop types through context-sensitive policy and business strategies. While this study ensures internal validity and reliability through systematic coding and stakeholder feedback, it acknowledges limitations in its generalisability. Future research may build on this work through comparative studies, longitudinal tracking, and direct engagement with nanostore owners and their communities to further understand the dynamics of their identity and their resilience in evolving retail landscapes. Full article

Buildings play a pivotal role in the daily functioning of cities, and the development of smart cities is intricately linked to the sustainable development of architectural practices. However, existing reviews have predominantly concentrated on the development of smart cities, often overlooking the interdisciplinary complexities associated with integrating smart city technologies and sustainable building practices. This study systematically reviews 418 relevant papers from the Web of Science database, employing both quantitative and qualitative analytical methods to assess the current status and future trajectory of the field. Therefore, it bridges a significant gap in the existing literature. The findings underscore the contributions of technologies such as the Internet of Things (IoT), artificial intelligence, and big data in enhancing the sustainability of buildings within smart cities. The key areas of focus include energy management, smart building systems, and resource optimisation. Furthermore, the study identifies emerging research themes, such as smart city buildings, smart energy management, and digital twins, highlighting their potential to optimise building performance and foster sustainability within evolving urban systems. The keywords identified in the current body of research are categorised into six main areas: context, objectives, methods, artificial intelligence, emerging technologies, and opportunities and challenges. Research themes are seen to progress from “performance” to “building” and “sustainability” and from “city” to “city” and “sustainability”. Notably, themes such as “city”, “modelling”, and “design” have evolved into themes centred around the “Internet”. However, with the rapid expansion of digital technologies, scholars must also address several critical challenges, including data security and privacy protection, the complexity of cross-system data coordination, uncertainties in sustainable optimisation processes, and the ethical and societal implications of technology adoption. To ensure the successful and sustainable development of future urban smart buildings, it is essential to establish rigorous data security standards, harmonise technical protocols, implement effective global strategies, and prioritise ethical considerations. In addition, unmanned technologies and their associated systems offer valuable insights into the sustainability of buildings in smart cities. Finally, this study presents a comprehensive and systematic framework that provides invaluable insights for future strategic planning and technological advancements in the field. Full article

Developing Age-Friendly Cities and Communities (AFCCs) is an increasingly popular policy response to supporting ageing populations. AFCC programmes rely on cross-sectoral collaboration, involving partnerships among diverse stakeholders working across sectors to address shared goals. However, there remains a limited understanding of what mechanisms and strategies drive collaboration among diverse actors within age-friendly cities. To address this gap, this empirical paper draws on examples from a comparative case study across Akita (Japan) and Manchester (UK), two cities with distinct demographic profiles but both with a longstanding commitment to the age-friendly approach. Case studies were created through a range of data collection methods, namely, a review of secondary data sources, semi-structured interviews with key stakeholders, and fieldwork in each city. Key insights from the case studies relating to the mobilisation of cross-sectoral collaboration were categorised into three themes: leadership and influencing, co-production, and place-based working. These mechanisms are not mutually exclusive; collaboration building through co-production and place-based working is essential to deliver age-friendly programmes, but these mechanisms rely on leadership and influence. Therefore, it is recommended that all three mechanisms be used to effectively mobilise cross-sectoral collaborations to collectively create AFCC and support healthy ageing. Full article

Accessibility to cultural heritage is crucial for fostering inclusive urban environments and preserving historical and cultural identities. This study addresses the gap between heritage conservation and urban accessibility with two objectives: (1) to identify tangible and intangible cultural heritage elements based on user preferences from the social media platform Foursquare, and (2) to assess the impact of accessibility on public engagement using Space Syntax analysis. The historic centres of Valencia and Alicante, Spain, were chosen as case studies for their rich cultural heritage and dynamic urban contexts. A novel urban cultural heritage (UCH) taxonomy was developed to categorise heritage elements into buildings, public spaces, elements, and events/festivities. Findings indicated that social media data offer valuable insights that complement official heritage catalogues, providing a richer understanding of cultural assets and public engagement. The results showed that higher public engagement was concentrated (1) in and around key heritage sites, (2) in heritage sites that combine cultural significance with multifunctional public use, (3) in public spaces and urban nodes that are highly accessible and well connected to the urban structure, (4) in areas where clusters of heritage elements are located close together, and (5) around sites of architectural prominence and cultural significance. This emphasised that accessibility is as important as historical significance for attracting public interest. The study suggested that improving accessibility and integrating social media data with traditional methods can enhance heritage conservation strategies and support sustainable urban development by fostering stronger identity values within cities. Full article

The positive energy district (PED) concept is attracting growing research interest; however, the need for practical approaches to facilitate their implementation remains crucial. This study, framed in the COST Action ‘Positive Energy Districts European Network’, offers a comprehensive review of the roadmaps, pathways, and guidelines—namely ‘PED-Transition Approaches’—currently available to support the implementation of district-scale innovative models, thereby advancing energy transitions and enhancing livability at the city level. The review involved a systematic search and web scraping of documents, including scientific and grey literature, as well as EU-funded projects’ reports. The studies were identified according to multiple filters and eligibility criteria, then categorised in a structured repository using a multidimensional matrix, and finally examined following three-levels of detail (i.e., bibliometric study) overview and in-depth analysis. The findings reflect the main characteristics, gaps, and challenges in PED implementation by underlying the growing need for effective step-by-step, user-centric, and context-based transition approaches. In conclusion, the research, building on an extensive literature of multiple inspirational methodologies and their associated use cases, is a strong basis to develop sequential pathways to facilitate PED implementation among key stakeholders in a short–medium-term perspective towards a climate-neutral city vision. Full article

The examination of land-use change simulations across a range of scenarios represents a pivotal research avenue for the advancement of sustainable development analysis. Nevertheless, the extant research merely categorises all building land in a land-use classification into a single category, which is unable to provide a detailed analysis of the dynamic internal spatial form of the city. This paper analyses 17 LCZ land-use types in Guiyang City in 2013 and 2022, and reclassifies them into 7 RLCZ land-use types based on the height of urban building sites. It also proposes three possible scenarios of BAU, WLC, and SPC in 2040 and simulates their land-use changes using the PLUS model. The results demonstrate that (1) the size of low-rise buildings in Guiyang has declined significantly over the past decade; (2) built-up land within cities is significantly affected by drivers such as night-time lighting, topography, elevation, and roads; (3) the SPC scenario emphasises a development pattern of land intensification and a focus on high density in urban built space. It also protects the stability of the ecosystem. The scenario can provide informative suggestions for spatial pattern changes in rapidly developing cities such as Guiyang. Full article

With the increase in climate-change-related hazardous events alongside population concentration in urban centres, it is important to provide resilient cities with tools for understanding and eventually preparing for such events. Machine learning (ML) and deep learning (DL) techniques have increasingly been employed to model susceptibility of hazardous events. This study consists of a systematic review of the ML/DL techniques applied to model the susceptibility of air pollution, urban heat islands, floods, and landslides, with the aim of providing a comprehensive source of reference both for techniques and modelling approaches. A total of 1454 articles published between 2020 and 2023 were systematically selected from the Scopus and Web of Science search engines based on search queries and selection criteria. ML/DL techniques were extracted from the selected articles and categorised using ad hoc classification. Consequently, a general approach for modelling the susceptibility of hazardous events was consolidated, covering the data preprocessing, feature selection, modelling, model interpretation, and susceptibility map validation, along with examples of related global/continental data. The most frequently employed techniques across various hazards include random forest, artificial neural networks, and support vector machines. This review also provides, per hazard, the definition, data requirements, and insights into the ML/DL techniques used, including examples of both state-of-the-art and novel modelling approaches. Full article