Search Results (4,215)

Following the launch of the Sustainable Development Goals (SDGs) process at the Rio+20 Summit, China has progressively strengthened sustainability-oriented considerations in development target setting and administration cadre performance assessment, which provides an institutional window to examine how the transformation of development goals reshapes urban land supply patterns. This study develops a spatial general equilibrium model and uses panel data for 286 prefecture-level cities in China from 2007 to 2021 to examine how the transformation of development goals affects urban land supply patterns. The results show that higher economic growth targets significantly expand total land supply, raise the ratio of industrial to residential land supply, and tighten floor-area-ratio (FAR) regulation. “Soft constraint” wording dampens the effect on land supply scale but strengthens the effects on land supply structure and FAR regulation, while the degree of vertical and horizontal target escalation generates substantial heterogeneity in these relationships. Moreover, after governance shifted from growth-oriented to sustainability-oriented objectives, the marginal effectiveness of using land supply structure and FAR regulation to deliver predetermined growth targets declined significantly. This study provides empirical evidence and policy-relevant insights for improving sustainability-oriented target accountability systems and urban governance incentive mechanisms. Full article

Technological advances are increasingly influencing how the public sector makes decisions according to citizens’ needs and the community’s problems. The need for a solution that facilitates the fast adaptation of administration to social context and people’s feedback becomes mandatory in order to ensure better services and implement projects that are in concordance with needs. In this paper, we propose a sandbox solution that helps public administration better understand community problems in real time, allocate public money more effectively to projects that really matter, and assess the administration’s performance. We started by collecting, filtering and analyzing social platforms posts and comments for 95 municipalities, and we extracted both the impressions/sentiment, but also the real problems that the communities are facing. Also, we categorized all cities depending on population, geographical area, and historical area to better identify common problems and create clusters of topics based on this split. We identified the most common issues communities face and integrated all the information into a sandbox that can be easily used by local administration for reactive decision-making and by central administration to provide a better overview of how public money is spent and whether the decisions align with needs. The results show that there is a real need for a sandbox to bring more clarity to the central and local administration layers and also better connect administrations with the people. Full article

Micromobility studies sustainable urban mobility. In this area, bicycles have been the most popular vehicle for several years. However, the recent growth of users of alternative mobility vehicles, such as stand-up electric scooters (e-scooters), has raised several questions on how they interact with the infrastructure and other users, as well as whether the existing infrastructure is suitable for these vehicles. One of the variables to be analyzed is riding comfort, which can be measured through the vibrations transmitted to users by the pavement. Thus, this paper presents a methodology to assess the comfort of the micromobility infrastructure based on the vertical accelerations registered by an instrumented e-scooter. This methodology has been applied in ten sections of the cycling infrastructure network of Valencia (Spain). The analysis showed that asphalt presented less vibrations than any other material, followed by concrete and square tiling alike, and finishing with transversely oriented cobblestones. This translates directly to comfort, with asphaltic pavements being more comfortable than any other. The analysis also showed that higher speeds mean higher vibrations. This proves to be a useful tool for infrastructure management, where the administrator can place more uncomfortable pavements to lower the riding speed in desired areas (e.g., schools). Full article

Background: The administration and management of humanitarian logistical operations are considered critical factors. The extreme and unexpected nature of events such as natural disasters poses logistical challenges to humanitarian support agencies providing aid to the affected area. These logistical challenges are characterized by fluctuations in demand that generate uncertainty in the required capacity for aid, all of which are emphasized at the last link in the humanitarian supply chain: the point of distribution for humanitarian aid (the so-called last-mile problem). The objective of this research work is to support the decision-making process regarding capacity adjustments and the closure of the distribution points established in the disaster area. Methods: In response, a Markovian Decision Model for Capacity Adjustment was developed, focused not only on reducing traditional logistics costs but also on minimizing human suffering by incorporating so-called deprivation costs. Results: The model establishes adjustment policies for capacity for each aid period, and the existence of a monotonous policy that establishes an optimal threshold for closure decisions was demonstrated. Conclusions: It is possible to efficiently adjust the capacity at the distribution points and minimize the costs (both logistical and deprivation) associated with each decision period. Full article

Background: Street sex workers (SSWs) experience some of the highest levels of health inequality in the UK, yet face persistent barriers to accessing NHS healthcare. These barriers are shaped by structural disadvantage, stigma, and the complex realities of their lives. Despite significant health needs, engagement with services remains low, and existing models of care often fail to accommodate the lived experiences of this population. Aims: This study explores how SSWs access, experience, and navigate NHS healthcare. It aims to understand the barriers and enablers of access, identify areas for improvement, and offer recommendations to inform the development of more inclusive service provision. Methods: An ethnographic approach was undertaken within a South Yorkshire charitable organisation. Data collection involved participant observation and an arts-based scrapbook intended to facilitate trauma-informed, flexible engagement. Thematic analysis was used to analyse the data, organised around a dynamic, processual approach using the candidacy framework. Findings: Barriers to care were present across all stages of healthcare engagement, including minimisation of health needs, administrative exclusion, lack of continuity, and stigma from professionals. Participants frequently described systems as inaccessible. Key enablers included supportive organisational staff and consistent, trusted relationships with specific providers. Areas for Improvement and Recommendations: Findings highlight the need to simplify registration processes, provide in-person options, and reduce reliance on digital communication. Greater continuity of care and gender-sensitive, trauma-informed approaches were consistently requested. Services should not be evaluated solely by uptake but by how well they accommodate marginalised users. Healthcare settings that prioritise safety, trust, and consistency were shown to improve engagement. SWs spoke of the work of accessing care, which for many was too hard to gain. Conclusions: SSWs are not disengaged from healthcare but are routinely excluded by systems that fail to meet their needs. Service redesign must begin from the realities of those who are most marginalised, through co-production, to reduce health inequity and build meaningful access. Full article

Rapid urbanization and global warming are amplifying heat-related health risks, particularly for vulnerable age groups. This study develops an open-source risk assessment framework that uses big data from remote sensing, land use, and population datasets to evaluate heat-related health risks. The framework integrates indicators of green infrastructure, Land Surface Temperature (LST), and demographic vulnerability to identify areas of increased health risk. Milan (Italy) was used as the case study for the application to test the methodology and validate its capacity to detect spatial correlations between Surface Urban Heat Island (Surface UHI) intensity and concentrations of sensitive population groups (children aged 0–5 and elderly aged 65+). The results highlight distinct spatial inequalities in heat exposure and health vulnerability, confirming the method’s potential to support climate adaptation and public health planning. By relying entirely on open-access data and tools, this approach offers a replicable and scalable model for assessing climate-related health risks and informing evidence-based strategies that can support public administrations to visualize risk, prioritize interventions, and enhance urban resilience. Full article

Effective management of transitional waters requires collaboration between administrative and scientific institutions, in line with the sustainable water management principles established by the Water Framework Directive (WFD, 2000/60/EC). The Cadiz and San Fernando salt marshes, classified as wetlands of international importance, currently exhibit an ecological and chemical status that is “worse than good.” However, there is still a lack of high-resolution, spatially explicit tools to identify where contaminants are most likely to accumulate in highly modified transitional waters, which limits effective monitoring and management strategies. This study aims to fill this gap by combining a high-resolution hydrodynamic model with a Lagrangian-particle-tracking approach to determine areas most vulnerable to contaminant accumulation from wastewater discharges. Simulations across multiple tidal cycles revealed that contamination is concentrated near discharge points and in low-flow channels, with tidal dynamics strongly influencing transport patterns. Key findings indicate that certain marsh sectors consistently experience higher contaminant exposure, highlighting priority areas for monitoring and management. The study provides novel insights by integrating modeling tools to produce a vulnerability classification of high-, medium-, and low-risk zones. These results contribute to the broader scientific understanding of contaminant dynamics in transitional waters and offer a transferable framework for improving wetland management in other heavily modified coastal systems. Full article

Post-disaster reconstruction requires instruments capable of ensuring procedural consistency, administrative transparency, and the systematic integration of geohazards, all of which are essential for safeguarding communities. This study presents the digital platform established under Italian Law 55/2019 for the reconstruction of the areas on Mt. Etna affected by the Mw 4.9 earthquake of 26 December 2018, emphasizing its innovative contribution to current international approaches to reconstruction governance. The platform standardizes the entire administrative workflow and is centered on the Parametric Form, which enables an objective calculation of eligible reconstruction grants based on damage indicators, vulnerability metrics, and parametric cost functions. A defining feature of the Etna model is the structural integration between administrative procedures and geohazard mitigation, achieved through updated hazard maps and protocols that incorporate geological, hydrogeological, and geomorphological conditions. This approach reframes reconstruction as an opportunity to reduce overall territorial vulnerability. The system also includes public monitoring tools (WebGIS and dashboards) that enhance traceability, compliance, and stakeholder engagement. Expected outcomes include shorter administrative timelines, improved interinstitutional coordination, and the potential transferability of the model to other emergency contexts. In comparison with international cases, the Etna experience represents an original integration of digitalization, parametric assessment, and site-specific hazard mitigation. Full article

In vitro models of the human nasal cavity are crucial for understanding the deposition dynamics of nasally administered drugs. Three-dimensional (3D) printing offers a powerful method for creating patient-specific, anatomically precise models for such experimental purposes. Background/Objectives: This study details the complete workflow for the development, design, and fabrication of a sectioned nasal cavity model intended for droplet deposition analysis of nasal sprays. Methods: A digital nasal cavity model was derived from medical imaging data and optimized for computer-aided design (CAD) operations. It was segmented into five therapeutically relevant regions: nasal vestibule, olfactory area, middle and upper turbinates, lower turbinate, and nasopharynx. Sections were 3D-printed in polypropylene for chemical compatibility, and a carbon fiber-reinforced fixation frame ensured precise alignment and airtight assembly. Results: Functional validation confirmed the model’s functional relevance through comparative deposition studies using automated actuation and high-performance liquid chromatography (HPLC) based regional quantification. Two devices with distinct spray characteristics (characterized separately by laser diffraction, plume geometry, and spray pattern imaging) were tested under varied administration conditions. The study demonstrated the model’s ability to discriminate between products, establishing a solid foundation for future investigations incorporating additional variables. Conclusions: Overall, the developed methodology provides a cost-effective and replicable platform for producing anatomically accurate, sectioned nasal cavity models. The newly developed in vitro system is well suited for detailed, region-specific analysis of nasal spray deposition, offering a valuable tool for pharmaceutical research and development. Full article

Accurate precipitation mapping is essential for effective disaster management; however, individual radar, satellite, and numerical weather prediction products often struggle in the topographically complex terrain of South Korea. This study proposes a high-resolution (~500 m) daily precipitation fusion framework that integrates Korea Meteorological Administration (KMA) radar, Global Precipitation Measurement (GPM) Integrated Multi-Satellite Retrievals for GPM (IMERG), and Local Data Assimilation and Prediction System (LDAPS) data. The framework employs a Random Forest model augmented with a monthly Empirical Cumulative Distribution Function (ECDF) correction. Auxiliary predictors are incorporated to enhance physical interpretability and stability, including terrain attributes to represent orographic effects, land-cover information to account for surface-related modulation of precipitation, and seasonal cyclic signals to capture regime-dependent variability. These predictors complement dynamic precipitation inputs and enable the model to effectively capture nonlinear spatiotemporal patterns, resulting in improved performance relative to individual radar, IMERG, and LDAPS products. Evaluation against Automated Synoptic Observing System (ASOS) observations yielded a correlation coefficient of 0.935 and a mean absolute error of 3.304 mm day⁻¹ in a Leave-One-Year-Out (LOYO) validation for 2024. Regional analyses further indicate substantial performance gains in complex mountainous areas, including the Yeongdong–Yeongseo region, where the proposed framework markedly reduces estimation errors under challenging winter conditions. Overall, the results demonstrate the potential of the proposed fusion framework to provide robust, high-resolution precipitation estimates in regions characterized by strong topographic and seasonal heterogeneity, supporting applications related to hazard analysis and hydrometeorological assessment. Full article

To host the 2022 Winter Olympics, Beijing and Zhangjiakou implemented extensive ecological restoration projects, improving the ecological quality of the region. However, detailed evidence of long-term spatiotemporal dynamics in vegetation productivity remains limited. This study employed the Carnegie–Ames–Stanford Approach (CASA) to estimate the vegetation Net Primary Productivity (NPP) in the Beijing–Zhangjiakou region from 2004 to 2023, utilizing 250 m monthly NDVI data. The 30 m resolution China Land Cover Dataset (CLCD) was incorporated to mask non-vegetated pixels and refine the vegetation mask, reducing mixed-pixel effects. Spatiotemporal variations, seasonal change-point detection, interannual stability, and trend persistence were analyzed across administrative regions and land cover types. Results indicate pronounced spatial heterogeneity in NPP, with persistently high values in forest-dominated western and northern Beijing and northeastern Zhangjiakou, and lower values concentrated in Beijing’s built-up and cropland-dominated southeastern plain. Pixel-level boxplots suggest stronger intra-regional variability in Beijing than in Zhangjiakou. Across landcover types, forests generally maintain the highest NPP, while grasslands are relatively lower. Boxplots further show that shrubs exhibit the highest variability, with all types showing right-skewed distributions. Annual mean NPP increased significantly for the entire region, Beijing, and Zhangjiakou, with interannual increase rates of 3.57, 1.56, and 4.53 gC·m⁻²·yr⁻², respectively; the lowest values occurred in 2007 and the highest in 2022. Trend maps and category statistics consistently suggest that positive trends dominate most of the region and expanded slightly during 2014–2023. BEAST analysis suggests a stable seasonal NPP cycle with no significant seasonal change points. CV-based assessment indicates generally high to extremely high stability, whereas low-stability zones are mainly associated with urban expansion areas, surrounding croplands, and parts of Zhangjiakou grasslands. Hurst results suggest that persistently increasing trends cover more than 90% of the study area, while persistently decreasing trends account for about 5.25% and are primarily linked to Beijing’s expansion zones. Full article

Chemotherapy is known to cause significant neutropenia, though concomitant left shift (also known as bandemia) has yet to be documented in dogs. The objective of this study is to assess the prevalence of band neutrophil elevation in dogs undergoing multiagent chemotherapy and identify factors influencing bandemia development. Medical records were retrospectively reviewed between 2018 and 2022 for dogs that started multiagent chemotherapy with at least one follow-up visit. Records were analyzed for body surface area (BSA), white blood cell count, segmented neutrophil count, band neutrophil count, and the previously administered chemotherapy drug (vincristine, cyclophosphamide, or doxorubicin). A generalized linear mixed model was used for statistical analysis. Ninety dogs with 530 nadir complete blood counts (CBCs) were identified. Band neutrophils were present in 20.2% of nadir CBCs, and increased band neutrophils occurred in 13.6%. Smaller BSA was associated with higher bandemia prevalence. Bandemia prevalence was 6% higher after vincristine (Risk Difference, 95% CI = [1%, 11%], p = 0.026) or doxorubicin (Risk Difference, 95% CI = [−1%, 13%], p = 0.115) administration than when patients received cyclophosphamide. Limitations include a lack of standardization of protocol, evaluation of underlying conditions that could contribute to bandemia, and opportunity for laboratory error. This study demonstrates that band neutrophils are present in dogs receiving chemotherapy, with a negative relationship between bandemia and BSA. Bandemia was most common following vincristine and doxorubicin administration. Full article

Background: In the treatment of ischemic stroke, both tissue-type plasminogen activator (t-PA) thrombolytic and endovascular therapy are employed; however, delayed intervention with these therapies increases the risk of hemorrhage. Hemorrhage associated with delayed t-PA treatment involves the activation of plasmin and matrix metalloproteinases (MMPs); however, the detailed mechanisms underlying I/R activation remain unclear. Objectives: This study examined the effects of delayed recanalization on ischemic stroke in a permanent middle cerebral artery (MCA) occlusion (MCA-O) model, and a novel MCA ischemia/reperfusion (I/R) model: 2-h ischemia followed by reperfusion (I/R 2 h), and 4.5-h ischemia followed by reperfusion (I/R 4.5 h). Secondary induced thrombus (SIT) formation, hemorrhage, MMP activity, MMP-9 immunoreactivity, and tomato lectin (TL) staining, as well as the effects of t-PA and heparin treatment were evaluated. Results: SIT formed within 1 h after reperfusion in the I/R 4.5 h model only, while t-PA or heparin treatment reduced SIT formation. Hemorrhage increased with or without t-PA administration in the I/R 4.5 h model, but it was suppressed by heparin pretreatment. MMP activity and MMP-9 immunoreactivity were localized to the SIT. Additionally, a negative staining area for TL was observed in the damaged area, where SIT formed in the I/R 4.5 h model. Conclusions: These results suggest that delayed recanalization induces SIT via glycocalyx degradation, leading to hemorrhage via plasmin/MMP-9 activation by endogenous and exogenous t-PA-mediated fibrinolysis in novel murine models of ischemic stroke. Furthermore, inhibition of SIT formation is beneficial for suppressing hemorrhages associated with delayed recanalization after endovascular or t-PA therapy. Full article

The frequency and intensity of tropical cyclones (TCs) in the Arabian Sea have increased in recent decades, heightening concerns regarding regional vulnerability and forecasting difficulties. This study examines the impact of the Madden–Julian Oscillation (MJO) on TCs activity—formation, frequency, and severity—over the Arabian Sea from 1982 to 2021. This study analyzes variations in convection, vertical wind shear (VWS), sea level pressure (SLP), and relative humidity (RH) across different MJO phases utilizing the best-track data from the India Meteorological Department (IMD), the Real-Time Multivariate MJO (RMM) index, and reanalysis datasets from the National Oceanic and Atmospheric Administration (NOAA) and the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR). Results show that more than 80% of TCs form during the convectively active phases of the MJO (P1–P4). These phases have the most noticeable negative outgoing longwave radiation (OLR) anomalies, as well as higher mid-level moisture and low-pressure anomalies, which are good for cyclogenesis. On the other hand, suppressed phases (P6–P8) have positive outgoing longwave radiation, dry air in the middle troposphere, and high-pressure anomalies, which make it harder for TCs to form. While VWS is predominantly favorable during both active and inactive phases, thermodynamic and convective factors principally regulate the modulation of TC activity. The simultaneous presence of active MJO phases with positive Indian Ocean Dipole (pIOD) and neutral or El Niño conditions markedly increases TC frequency, highlighting a combined influence link between interannual–El Niño–Southern Oscillation (ENSO) and IOD– and intraseasonal (MJO) variability. Additionally, the association between MJO and the Indo-Pacific Warm Pool (IPWP) reveals that TC activity peaks during convectively active MJO phases under the second twenty years of this study, emphasizing the influence of large-scale oceanic warming on TC variability. These findings underscore the critical function of the MJO in regulating TC activity variability in the Arabian Sea and stress its significance for enhancing intraseasonal forecasting and disaster preparedness in the area. Full article

The growing importance of cross-border scientific collaboration reflects its role in strengthening regional innovation systems and supporting sustainable socio-economic development. This study examines cross-border scientific research collaboration between Shenzhen and Hong Kong, with particular attention to how institutional differences impact the sustainable development of such cooperation. Drawing on the analytical framework of the cross-border regional innovation systems (CBRIS), this study employs qualitative research methods—including fieldwork interviews, focus groups, and thematic workshops—to systematically examine the key challenges and emerging opportunities arising from institutional differences between the two regions. The findings show that there are significant institutional differences in four areas, including research integrity systems, scientific resource sharing mechanisms, project management processes, and talent development frameworks. These distinctions not only undermine the effectiveness of cross-border collaboration, but they also offer opportunities for institutional coordination and policy innovation meant to promote a more inclusive and sustainable regional research cooperation system. By analysing the experiences of researchers and research administrators, the study emphasises the crucial importance of institutional coordination in ensuring the long-term sustainability of the CBRIS. The results offer data-based evidence and policy insights that can inform the development of policy innovations to strengthen cross-border scientific collaboration and promote the sustainable evolution of the CBRIS. Full article