Search Results (443)

Building materials and their spatial distribution play a significant role in determining the outcomes of human-caused and natural disasters in urban and peri-urban areas. However, building-level data on building and roofing materials are scarce. Here, we explore the feasibility and performance of a Convolutional Neural Network (CNN) model using spectrally transformed high-resolution multispectral imagery to map roofprints (i.e., classifying and delineating roofing materials at the building footprint-level) in Washington, District of Columbia (D.C.) and Denver, CO, United States. To generate consistent training data, we integrate geospatial vector data of individual building footprints with real estate industry-derived building-level roofing material data to create labeled image data from Planet SuperDove imagery. We compare the CNN classifier to a pixel-based machine learning (ML) model to demonstrate the capability of our roofprints mapping approach. With F1-scores ranging from 0.56 to 0.95 for the most common roof material classes, the CNN model outperformed the pixel-based ML classifier by 15% and 17% in Washington, D.C., and Denver, respectively. Results demonstrate within-domain robustness for the studied metropolitan areas, which are characterized by differing building densities, roof morphologies, and material patterns. While cross-region transferability was not evaluated, our findings provide a controlled comparison of pixel-based and context-aware approaches for rooftop material mapping and highlight the importance of hierarchical representations that integrate spectral information with roof texture, edge characteristics, spatial arrangement, and neighborhood context for improving classification performance. Accurately mapping building materials has the potential to advance urban planning and environmental policies, including assessments of heat exposure, energy demand, as well as hazard risk and community resilience. Full article

Functional gastrointestinal disorders (FGIDs) affect over 40% of the global population and represent a substantial health and economic burden. Gandhaga Dravagam (GD) is a classical Siddha mineral-based distillate prepared from sulfur, potassium nitrate, and alum, traditionally indicated for gastrointestinal complaints such as diarrhea, indigestion, and colonic spasm. This study aimed to standardize GD using organoleptic and physicochemical evaluation, qualitative acid-radical and basic-radical tests, elemental analysis by Inductively Coupled Plasma-Optical Emission Spectrometry (ICP-OES), and X-ray Diffraction (XRD), as well as to assess its antispasmodic potential against acetylcholine (ACh)-induced contractions in an isolated rat ileum model. GD was a clear acidic liquid (pH 2.05 at 10% aqueous dilution) with a specific gravity of 1.0142 at 25 °C. Qualitative analysis confirmed carbonate, sulfate, phosphate, and nitrate radicals. ICP-OES identified sulfur (501.254 mg/L) as the predominant element, followed by aluminum (155.341 mg/L), potassium (100.121 mg/L), phosphorus (56.341 mg/L), and sodium (1.320 mg/L); arsenic, mercury, lead, manganese, and magnesium were below detection limits. XRD revealed crystalline inorganic phases consistent with the sulfur-, potassium-, and aluminum-based constituents. At a single concentration (2% v/v), GD reduced ACh-induced contractile responses by 40.74–56.25% across all ACh concentrations tested (5–80 µg), indicating a consistent antispasmodic effect. These findings provide a preliminary analytical and pharmacological characterization of GD and warrant further mechanistic, toxicological, and clinical evaluation. Full article

This study examines how ESG performance, innovation performance, and policy support relate to organizational resilience in China’s real estate industry. Drawing on the Resource-Based View, Institutional Theory, and Configurational Theory, organizational resilience is conceptualized through recovery and resistance capacities. Fixed-effects regression, robustness tests, and heterogeneity analyses are applied using panel data from 80 Chinese A-share-listed real estate firms from 2015–2024 (800 firm-year observations). The findings show that ESG performance is positively associated with accounting-based recovery, particularly Return on Equity, but negatively affects market-based recovery in the baseline models, reflected in Tobin’s Q. Additional analysis reveals a U-shaped relationship between ESG performance and Tobin’s Q, suggesting that initial market valuation penalties may decline as ESG engagement deepens. Innovation performance shows limited baseline effects but becomes more relevant in alternative specifications related to recovery and leverage. Policy support, measured through tax rebates (TAX), did not show significant direct effects on organizational resilience in the baseline models. However, robustness analyses using green expenditure intensity (GEx) suggest possible indirect and conditional policy-related mechanisms associated with sustainability-oriented investment behavior. Overall, organizational resilience is shaped by heterogeneous interactions among ESG, innovation, and policy-related factors. Full article

Linear speed is a key performance determinant in ice hockey, yet no studies have compared continuous on-ice and off-ice velocity profiles across multiple competitive levels. This study examined continuous velocity curves and discrete sprint variables during 20 m on-ice (skating) and off-ice (running) sprints across three competitive levels. Sixty male ice hockey players (A-Team n = 20, U20A n = 20, U20B n = 20) completed maximal 20 m sprints in both conditions using a motorized resistance device. Bayesian analyses were used to evaluate continuous velocity profiles and discrete variables. Posterior estimates consistently favored greater off-ice velocity profiles than on-ice velocity profiles across all groups, particularly during the early portion of the sprint (P(diff) ~85%), although the practical meaningfulness of these differences remained uncertain. Discrete sprint variables showed stronger and more consistent practically meaningful differences (P(diff > SWC) = 66–99%). Between-group comparisons suggested a competitive hierarchy, with posterior estimates favoring greater velocity values in adults than lower competitive-level late adolescents (P(diff) ~87%). Practitioners should consider potential differences between on-ice and off-ice sprint performance and hierarchical trends across competitive levels when structuring training and assessment. Continuous velocity profiling may provide additional insight into velocity-development patterns, whereas discrete metrics may be more appropriate for routine team-level monitoring. Full article

Misuse of over-the-counter (OTC) and prescription-only medicines (POMs) is increasingly recognised as a public health and medicine-safety concern. Although specialist substance misuse services (SMS) increasingly support people affected by OTC/POM misuse, little is known about how SMS staff perceive the characteristics, challenges, and treatment needs of this population. This study explored the experiences of SMS staff to address this evidence gap and inform pharmacy practice and service development. Confidential semi-structured interviews were conducted with staff across five community adult English SMS. Audio recordings were transcribed verbatim and analysed thematically using NVivo^®. Twenty interviews with varied professionals achieved data saturation. Three overarching themes emerged: (1) characteristics of OTC/POM misuse; (2) staff-perceived patterns among people who misuse OTC/POM; and (3) negative experiences and concerns. Dependence on orally administered opioids (particularly codeine-containing products), benzodiazepines and gabapentinoids predominated. Polypharmacy including illicit substance use was also reported. Withdrawal symptoms frequently perpetuated misuse, and abrupt supply cessation created additional risks. Routine enquiry about OTC/POM misuse and provision of tailored harm-reduction interventions are essential. The findings suggest that pharmacists may have an important role in early identification of problematic OTC/POM use, harm-reduction interventions, medicine review and facilitating referral into appropriate treatment pathways. Further research should examine whether dedicated OTC/POM pathways are required and explore differences in demographic and treatment needs across medicine types. Full article

The development of eco-friendly magnesium (Mg)-based materials that possess acceptable mechanical properties, good biodegradability, and non-toxicity in biomedical applications has become more attractive in recent years, particularly for engineering and biomedical applications. This work investigates the effects of nano-ZnO (2 wt.%) reinforcement and cryogenic treatment (CT) on the microstructural, mechanical, thermal, and corrosion behavior of a non-toxic Mg-1Zn-1Ca alloy. Disintegrated melt deposition (DMD) was the synthesis starting point, while refrigeration at −20 °C (RF20) and liquid-nitrogen exposure at −196 °C (LN) were employed as the CT methods. CT significantly refined the grain size of the alloy and composite materials by more than 31.3%, down to 4.4–4.5 μm in diameter, leading to enhanced mechanical performance through grain boundary strengthening. RF20-treated Mg-1Zn-1Ca alloy exhibited the best damping properties (attenuation coefficient and damping capacity improved by 52.1% and 48.7%, respectively). Compressive response was also improved due to the combined effect of refined grains and reinforcement, with LN-treated Mg-1Zn-1Ca-2ZnO exhibiting the best combination of compression properties, i.e., YS—165 MPa, UCS—634 MPa, ε—43.6%, and W_f—175 MJ/m³. Ignition resistance was also improved with the addition of ZnO reinforcement (3.8% increase in ignition temperature). A significant reduction in corrosion rate was achieved with RF20 treatment, leading to corrosion rate reductions of 62% and 40% in PBS (simulated human body fluid) and salt solution, respectively, primarily due to equiaxed grains and stable microstructure. These results demonstrate the efficacy of ZnO reinforcement and CT conducted at different temperatures in selectively enhancing and tailoring the properties of eco-friendly, biocompatible Mg-alloys and composites for biomedical and strength-based applications. Full article

Plastic pollution is a problem for many municipalities, water authorities, and industries, including transportation, energy, agriculture, fisheries, real estate, tourism, hospitality, insurance, and healthcare. Efforts to understand and mitigate plastic pollution would benefit from a dedicated map satisfying basic criteria including traceability, scalability, spatio-temporal resolution, and data flexibility. This article details and demonstrates how several existing pollution maps satisfy these criteria and makes recommendations on their use for specific activities, including temporal monitoring, root-cause analysis (RCA), cleanups, and tourism guides. Advantages of using plastic density rather than piecewise logs as the primary data format are highlighted, in particular feasible memory requirements and access to cloud data. Environmental plastic mapping by passive optical sensors, which offer the potential of comprehensive qualified data, is also surveyed, including demonstration of an original shortwave infrared (SWIR) polarization imager, and dynamic plastic pollution monitoring is demonstrated through the application-programming interface (API) of the Google Maps platform utilizing both sensor and published survey data. Full article

This paper shifts the research perspective from “Buddhist monasteries” to “monastic Buddhism,” using Nālandā Mahāvihāra as a micro-level case to illuminate the broader support mechanism of Indian Buddhist monasteries, with particular focus on the concept of “non-exhaustible endowment”. Drawing on epigraphic evidence, Vinaya texts, and Chinese pilgrims’ records, it finds that major donors supported monasteries through religious rituals, land grants, and cash investments, primarily in the form of landed property and gold and silver currency, which were designated as non-exhaustible endowments. Monasteries then engaged in agriculture, handicrafts, building industry, commerce, and lending, transforming static assets into a non-exhaustible cycle of capital that benefited both monastics and laity. Systems such as Yizhi (robe funds) and Gongfu zhi Zhuang (robe-providing estates) reveal mature financial services that not only liberated monks from economic constraints but also stimulated the cotton textile trade between India and China. The wealth possessed by monasteries was not static but perpetually engaged in a dynamic cycle of capital. Major Buddhist monasteries thus emerged as regional economic engines, which became the core value for continuous royal patronage, as well as the key incentive for their violent destruction by Turkic Muslims. However, the transformation of the religious landscape and economic network in late medieval Bihār was not a simplistic process. Faced with a changing political and religious environment over time, Sufi saints, Jain followers, Shaiva ascetics and other religious communities, each grounded in their own faiths, landholdings, commercial networks and educational systems, gradually displaced, restructured and undermined the Buddhist monastery-centered endowment mechanism, causing Buddhism to progressively lose its regional dominance as an institutionalized religion. Full article

The rapid expansion of housing financialization (REF) has profoundly reshaped China’s subnational fiscal landscape, yet the dynamic nature of this relationship remains under-explored. This study investigates how the impact of REF on fiscal deficits (DB) evolves over time and identifies the specific transmission channels mediating this influence. First, we construct a multidimensional REF index by integrating enterprise, household, market, financial, and industry indicators via the fuzzy-TOPSIS method. A Markov Regime Switching model identifies three distinct volatility regimes, revealing that REF dynamics are highly sensitive to policy shifts and exhibit significant path dependency. Second, using a Time-Varying Parameter Vector Autoregression model, we find that REF initially functioned as a fiscal stabilizer providing short-term revenue relief; however, as financialization deepened, REF transformed into a procyclical driver of deficit expansion. Third, we further decompose this mechanism, demonstrating that land finance (LAND) and local government debt (UID) amplify systemic fiscal fragility as dynamic mediating channels. Finally, due to the unsustainability of the current “real estate-land-debt” model, we propose policy interventions including the institutionalization of fiscal-debt firewalls, the formation of counter-cyclical fiscal risk reserve funds, and an accelerated transition toward a stable, tax-oriented revenue structure to mitigate systemic risks. Full article

Existing research on the landscape patterns of urban parks and green spaces demonstrates a disproportionate focus across tiers within China’s urban hierarchy. Numerous studies have concentrated on economically developed first-tier cities, such as Beijing, Shanghai, and Guangzhou. In contrast, medium-to-large non-first-tier cities, especially provincial capitals and emerging cities within the first- and second tiers, have been relatively understudied, although they have received increasing attention in recent years. This bias extends regionally, with studies predominantly examining cities in the more developed central and eastern regions, while less-developed areas and lower-tier cities receive significantly less attention. This study tracks changes in park quantity, spatial concentration, patch structure and driver associations at three planning-related time points. Shenyang provides a distinct cold-region and old industrial city case, shaped by long winters, industrial renewal and outward urban growth. Furthermore, to inform park and green-space planning in Northeast China’s cold-climate cities, exemplified here by Shenyang, a major metropolis with a monsoon-influenced humid continental climate (Köppen Dwa), long cold winters, and relatively short warm summers, we document a shift in park distribution from the urban core to peripheral areas. Based on park vector layers reconstructed from planning documents, remote sensing interpretation and field verification, this study combined spatial analysis, landscape metric calculation and driver-association modeling. ArcGIS Pro was used to identify changes in distribution centers, directional extension and local clustering; FRAGSTATS 4.2 was used to calculate park landscape metrics; and SIMCA-P 14.1 was used to examine the statistical associations between selected landscape indicators and potential driving variables. The results show that the number and total area of parks in central Shenyang increased substantially from 2000 to 2024. Spatially, park distribution became less concentrated in the traditional inner city, while new clusters gradually appeared in peripheral districts and newly developed urban areas. The old urban core remained important, but its dominance weakened as park provision expanded outward. The landscape metric results further indicate that park expansion was accompanied by more irregular patch forms, stronger fragmentation and declining structural continuity. The driver association analysis suggests that climate conditions, population change, industrial restructuring, real estate investment, road construction and urban greening policies were related to different aspects of park landscape change. These associations should be interpreted as statistical relationships rather than direct causal effects. Overall, this study clarifies the spatial restructuring of park green spaces in a cold-region old industrial city and provides planning evidence for improving park connectivity, coordinating green space expansion with urban construction and supporting sustainable park system development in Northeast China. Full article

The global landscape of sustainability challenges has become increasingly complex, characterized by varying regulatory frameworks and market maturity across different nations. The financial significance of environmental, social, and governance (ESG) factors is influenced by industry and firm-specific attributes. Therefore, this study employs an integrated decision support framework that combines grey relational analysis (GRA) models including Deng’s GRA, absolute GRA, and a second synthetic grey relational analysis (SSGRA) with firm-level panel regressions to compare ESG and financial performance linkages across 11 Middle East and Africa (MEA) countries and industrial sectors. Furthermore, the study utilized a sensitivity analysis to check the robustness of SSGRG. Results indicate considerable variability in the relationships between ESG and financial performance across the region. The economies of the Gulf Cooperation Council (GCC) showed the most robust positive relationship between ESG factors and financial performance based on SSGRG, with Kuwait (0.82), Qatar (0.81), and Saudi Arabia (0.80) predominantly influenced by the social and governance dimensions. Conversely, a weak correlation was demonstrated in Egypt (0.54), Nigeria (0.53), and Kenya (0.56). Moreover, financials, communication services, and materials sectors exhibit the greatest integration of ESG factors into financial performance, with composite SSGRG values ranging from 0.75 to 0.78. In contrast, the information technology and energy sectors demonstrate weak association, with composite SSGRG values falling below 0.60. Furthermore, a conservative maximin analysis reveals that corporate governance in Kenya and environmental performance in Oman are identified as the weakest relationship at the country level, while governance in the information technology and energy sectors, environmental management in real estate, and social performance in consumer discretionary sectors are highlighted as weak connections. This study addresses a gap in the literature by developing a novel decision-support framework, providing fresh empirical evidence from emerging markets, and offering theoretical insights into the into influence of stakeholder and institutional factors on ESG value creation. This study provides implications for investors, corporate managers, and policymakers on sustainable finance in emerging markets and presents a decision-making framework that emphasizes ESG initiatives to enhance financial performance. Full article

This short communication synthesizes evidence on how the Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) altimetry data are used by private sector actors and the implications for economic value creation. Using secondary research that collected and summarized information from existing data from reports, journals, websites, and databases, the work identifies 54 companies across 9 sectors leveraging ICESat-2-derived elevation, canopy height, bathymetry, and surface measurements to inform decision-making, risk assessment, and new business models. The analysis situates ICESat-2 within a broader context where freely available Earth observation data can generate substantial private- and public-sector value, potentially exceeding hundreds of billions in aggregate when scaled across industries such as geospatial services, climate management, real estate, and insurance. The paper uses a four-pillar conceptual model to guide valuation of data-driven impacts: Data Utility (intrinsic information value of altimetry and related metrics), Decision Impact (tangible economic benefits from improved models and operations), Strategic Integration (emergence of new business models and market opportunities), and Data Ecosystem Exclusivity (development of proprietary datasets and workflows that enable competitive differentiation). Empirical findings illustrate how these pillars manifest in practice. The paper seeks to connect private-sector uptake to NASA’s Earth Science to Action framework and related capacity-building efforts, highlighting pathways for broader utilization through training, tutorials, and accessible interfaces. Limitations of the study include partial sector coverage and reliance on publicly reported use cases. Future work should quantify economic returns with standardized metrics and extend the dataset to capture dynamic shifts in data products, governance, and IP development within the evolving data ecosystem. Full article

Peptide-based supramolecular hydrogels have emerged as promising biomaterials due to inherent biocompatibility, tunable self-assembly, and structural similarity to the extracellular matrix. This work describes the design, synthesis and characterization of a library of symmetrical bolaamphiphiles based on dehydropeptides, systematically varying both the dehydroamino acid residue and the linker. Aromatic and aliphatic dicarboxylic acids with distinct rigidities were employed to elucidate their influence on molecular self-assembly, hydrogelation, and functional performance. Hydrogel formation was triggered using a pH-responsive approach, and critical aggregation and gelation concentrations were determined. Morphological analysis by transmission electron microscopy revealed dense fibrillar networks with nanometer-scale fiber diameters, while rheological studies demonstrated viscoelastic behavior, tunable mechanical strength, and, in selected systems, efficient self-healing properties. The incorporation of phenylalanyldehydrophenylalanine significantly enhanced hydrogel formation, highlighting the importance of π–π interactions and hydrophobicity. Biological evaluation using HaCaT keratinocytes confirmed low cytotoxicity across the series. A representative injectable hydrogel exhibited sustained release of the anticancer drug methotrexate, governed predominantly by Fickian diffusion. These results establish clear structure–property–function relationships and demonstrate the potential of symmetrical bolaamphiphilic dehydropeptides as versatile platforms for controlled drug delivery. Full article

Over the last decade, prefabrication has emerged as a strategic alternative to address the global construction industry’s challenges concerning sustainability, productivity, and the housing deficit. This study analyzes the advances, benefits, limitations, and research gaps associated with its application in real estate projects between 2015 and 2025. A systematic literature review was conducted under the PRISMA protocol, which allowed for the selection of 58 high-quality articles sourced from Scopus, Web of Science, SciELO, and Redalyc. The findings highlight Asia as the leader in innovation and industrialization, while Latin America is identified as an emerging region with applications in social housing, education, and modular infrastructure. Reported benefits include reduced time and costs, improved environmental performance, and the integration of digital technologies such as BIM, 3D printing, and digital twins. Nevertheless, regulatory gaps, cultural resistance, and limited coordination among industry, government, and academia persist. The study concludes that prefabrication constitutes a transformative engine for the real estate sector, but its consolidation requires stronger regulatory frameworks, broader empirical research in Latin America, and the adoption of circular economy and digitalization strategies to ensure a sustainable and socially accepted impact. Full article

In China, ports have long served as a key engine of growth for coastal cities. Increases in coastal port throughput inevitably lead to port spatial expansion, which in turn drives construction land expansion in port cities. Consequently, ports are a critical factor shaping construction land expansion in coastal cities, with direct implications for spatial planning and sustainable development in coastal port cities. Therefore, it is necessary to examine how ports influence construction land expansion in coastal cities. This paper using multiple linear regression and binary logistic regression models and incorporating landscape metrics explores the impacts of ports on the expansion of urban construction land in coastal port cities. The findings reveal distinct characteristics of land expansion in port cities compared to non-port cities: (1) Macro-level changes: The expansion of construction land is driven by industrial restructuring, real estate development, port cargo traffic, population growth, and GDP growth. Industrial restructuring is the primary driver, while real estate development plays a significant role in land expansion. Port cargo demand serves as a unique driving factor compared to non-port cities, whereas population and GDP growth have minimal effects. (2) Micro-level spatial expansion: Land expansion is influenced by proximity to port shorelines, transportation infrastructure, and the degree of base construction land expansion. Expansion tends to concentrate along the port shoreline, transport hubs, and established urban areas. Elevation and slope are significant factors for coastal port cities, while rivers and proximity to core urban areas predominantly impact estuarine port cities. (3) Temporal patterns of expansion: Port development follows a phased pattern of land expansion: “Decline → Increase → Decline”. Ports also influence landscape patterns, with increased distance from the port shoreline leading to decreased patch density and higher landscape fragmentation. The results of this paper help to address gaps in existing research on how ports shape the spatial expansion of coastal cities. Furthermore, this paper provides insights for effective land use strategies, spatial planning, and port-city management, promoting coordinated land and marine development. It offers a foundation for addressing the integration of land and sea spatial planning in the “One Map” initiative. Full article