Search Results (22,717)

Electric bikes (e-bikes) offer a low-carbon, space-efficient solution for campus mobility, yet their sustainable potential is increasingly challenged by patterns of non-compliant use, including speeding, informal parking, and unauthorized charging. This study integrates the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM) to examine the cognitive and contextual factors that shape such behaviors among university students. Drawing on a survey of 408 e-bike users and structural equation modeling, the results show that non-compliance is primarily driven by perceived usefulness, ease of action, and behavioral feasibility, with affective and normative factors playing indirect, reinforcing roles. Importantly, actual behavior is influenced not only by intention but also by students’ perceived capacity to act within low-enforcement environments. These findings highlight the need to align behavioral perceptions with sustainability goals. The study contributes to sustainable mobility governance by clarifying key psychological pathways and offering targeted insights for designing perception-sensitive interventions in campus transport systems. Furthermore, by promoting compliance-oriented campus mobility, this research highlights a pathway toward enhancing the resilience of transport systems through behavioral adaptation within semi-regulated environments. Full article

The global Black Lives Matter movement and COVID-19 pandemic drew attention to the urgency of addressing entrenched structural dynamics such as racialization, gender, and colonization shaping health inequities for diverse racialized people. Canadian community-based research with racialized immigrant women recognized the need to enhance service provider capacity using a strengths-based activism approach to support client health and wellbeing. In this study, we aimed to understand the impacts of this mental health promotion practice on service providers and strategies to support them. Through purposeful convenience sampling, three focus groups were completed with 19 service providers working in settlement and mental health services in Toronto, Canada. Participants represented varied ethnicities and work experiences; most self-identified as female and racialized, with experiences living as immigrant women in Canada. Postcolonial feminist and critical mental health promotion analysis illuminated organizational and structural dynamics contributing to burnout and vicarious trauma that necessitate a focus on trauma- and violence-informed care. Transformative narratives reflected service provider resilience and activism, which aligned with and challenged mainstream biomedical approaches to mental health promotion. Implications include employing a postcolonial feminist lens to identify meaningful and comprehensive anti-oppression strategies that take colonialism, racialization, gender, and ableism and their intersections into account to decolonize nursing practices. Promoting health equity for diverse racialized women necessitates focused attention and multilevel anti-oppression strategies aligned with critical mental health promotion practices. Full article

The retrofitting of legacy systems enables upgrades that extend the lifespan of outdated equipment, improve efficiency, and reduce environmental impacts. This manuscript builds on existing approaches to retrofitting legacy systems using Industry 4.0 technologies. Therefore, it explores how the proposed modernization envisions the transition from Industry 4.0 to Industry 5.0, which emphasizes human-centric approaches, sustainability, and resilience. Tools such as RAMI 4.0 (a reference architecture model for Industry 4.0), Lean Six Sigma (a methodology for process improvement), and Big Data analytics are highlighted throughout the text as essential for optimizing processes and ensuring alignment with global challenges, including resource efficiency and environmental sustainability. This work addresses both conceptual and technical aspects of system modernization. It provides a comprehensive framework for retrofitting systems and integrating advanced technologies such as digital twins. These efforts ensure that industries are prepared for the evolving demands of Industry 4.0 and beyond. Full article

Osteosarcoma (OS) is the most common primary bone malignancy in children and adolescents, which is also considered an aggressive disease due to its rapid growth rate, ability to metastasize early, and complex and heterogeneous tumor microenvironment (TME). Although we are developing improved surgical and chemotherapeutic approaches, the presence of metastatic or recurrent disease is still detrimental to the patient’s outcome. Major advances in understanding the molecular mechanisms of OS are needed to substantially improve outcomes for patients being treated for OS. This review integrates new data on the molecular biology, pathophysiology, and immune landscape of OS, as well as introducing salient areas of tumorigenesis underpinning these findings, such as chromothripsis; kataegis; cancer stem cell dynamics; and updated genetic, epigenetic, and glycosylation modifiers. In addition, we review promising biomarkers, diagnostic platforms, and treatments, including immunotherapy, targeted small molecule inhibitors, and nanomedicine. Using genomic techniques, we have defined OS for its significant genomic instability due to TP53 and RB1 mutations, chromosomal rearrangements, and aberrant glycosylation. The TME is also characterized as immunosuppressive and populated by tumor-associated macrophages, myeloid-derived suppressor cells, and regulatory T cells, ultimately inhibiting immune checkpoint inhibitors. Emerging fields such as glycomics and epigenetics, as well as stem cell biology, have defined promising biomarkers and targets. Preclinical studies have identified that glycan-directed CAR therapies could be possible, as well as metabolic inhibitors and 3D tumor models, which presented some preclinical success and could allow for tumoral specificity and enhanced efficacy. OS is a biologically and clinically complex disease; however, advances in exploring the molecular and immunologic landscape of OS present new opportunities in biomarkers and the development of new treatment options with adjunctive care. Successful treatments in the future will require personalized, multi-targeted approaches to account for tumor heterogeneity and immune evasion. This will help us turn the corner in providing improved outcomes for patients with this resilient malignancy. Full article

Salinity is a major abiotic stress limiting black gram (Vigna mungo) productivity, particularly in arid and semi-arid regions. Saline soils negatively impact plant growth, nodulation, nitrogen fixation, and yield. This study evaluated the efficacy of co-inoculating salt-tolerant plant growth-promoting bacteria Paenibacillus sp. SPR11 and Bradyrhizobium yuanmingense PR3 on black gram performance under saline field conditions (EC: 8.87 dS m⁻¹; pH: 8.37) with low organic carbon (0.6%) and nutrient deficiencies. In vitro assays demonstrated the biocontrol potential of SPR11, inhibiting Fusarium oxysporum and Macrophomina phaseolina by 76% and 62%, respectively. Germination assays and net house experiments under 300 mM NaCl stress showed that co-inoculation significantly improved physiological traits, including germination rate, root length (61.39%), shoot biomass (59.95%), and nitrogen fixation (52.4%) in nitrogen-free media. Field trials further revealed enhanced stress tolerance markers: chlorophyll content increased by 54.74%, proline by 50.89%, and antioxidant enzyme activities (SOD, CAT, PAL) were significantly upregulated. Electrolyte leakage was reduced by 55.77%, indicating improved membrane stability. Agronomic performance also improved, with co-inoculated plants showing increased root length (7.19%), grain yield (15.55 q ha⁻¹; 77.04% over control), total biomass (26.73 q ha⁻¹; 57.06%), and straw yield (8.18 q ha⁻¹). Pod number, seed count, and seed weight were also enhanced. Nutrient analysis showed elevated uptake of nitrogen, phosphorus, potassium, and key micronutrients (Zn, Fe) in both grain and straw. To the best of our knowledge, this is the very first field-based report demonstrating the synergistic benefits of co-inoculating Paenibacillus sp. SPR11 and Bradyrhizobium yuanmingense PR3 in black gram under saline, nutrient-poor conditions without external nitrogen inputs. The results highlight a sustainable strategy to enhance legume productivity and resilience in salt-affected soils. Full article

This study presents a 39-year spatiotemporal analysis of shoreline variability at Topocalma Beach (Chile) using satellite-derived data collected between 1985 and 2024. A total of 350 satellite images were processed with CoastSat and DSAS v6.0 to quantify erosional and accretional trends across distinct beach sectors. The results show persistent erosion in the proximal zone near the Topocalma wetland and localized accretion in the distal (southern) segment. These changes are closely associated with the 2010 Maule earthquake and tsunami, strong ENSO phases, and an increase in storm surge activity since 2015. The spatiotemporal beach width model reveals distinct phases of retreat and short-term post-seismic stabilization, followed by a shift to sustained erosion. Overall, this study underscores the limited natural recovery capacity of the beach and highlights the utility of satellite-based monitoring tools for coastal resilience planning in data-limited regions. Full article

Based on the panel data of daily meteorological stations and winter wheat yield in Henan Province from 2000 to 2023, this study comprehensively used the Mann–Kendall trend test, wavelet coherence analysis (WTC), and other methods to reveal the temporal and spatial evolution of extreme precipitation and its multi-scale stress mechanism on grain yield. The results showed the following: (1) Extreme precipitation showed the characteristics of ‘frequent fluctuation-gentle trend-strong spatial heterogeneity’, and the maximum daily precipitation in spring (RX1DAY) showed a significant uplift. The increase in rainstorm events (R95p/R99p) in the southern region during the summer is particularly prominent; at the same time, the number of consecutive drought days (CDDs > 15 d) in the middle of autumn was significantly prolonged. It was also found that 2010 is a significant mutation node. Since then, the synergistic effect of ‘increasing drought days–increasing rainstorm frequency’ has begun to appear, and the short-period coherence of super-strong precipitation (R99p) has risen to more than 0.8. (2) The spatial pattern of winter wheat in Henan is characterized by the three-level differentiation of ‘stable core area, sensitive transition zone and shrinking suburban area’, and the stability of winter wheat has improved but there are still local risks. (3) There is a multi-scale stress mechanism of extreme precipitation on winter wheat yield. The long-period (4–8 years) drought and flood events drive the system risk through a 1–2-year lag effect (short-period (0.5–2 years) medium rainstorm intensity directly impacted the production system). This study proposes a ‘sub-scale governance’ strategy, using a 1–2-year lag window to establish a rainstorm warning mechanism, and optimizing drainage facilities for high-risk areas of floods in the south to improve the climate resilience of the agricultural system against the background of climate change. Full article

With the acceleration of urbanization in China, water resources have become a key factor restricting regional sustainable development. Current research primarily examines the temporal or spatial variations in the water resources ecological footprint (WREF), with limited emphasis on the integration of both spatial and temporal scales. In this study, we collected the data and information from the 2005–2022 Statistical Yearbook and Water Resources Bulletin of the Yangtze River Delta Urban Agglomeration (YRDUA), and calculated evaluation indicators: WREF, water resources ecological carrying capacity (WRECC), water resources ecological pressure (WREP), and water resources ecological surplus and deficit (WRESD). We primarily analyzed the temporal and spatial variation in the per capita WREF and used the method of Geodetector to explore factors driving its temporal and spatial variation in the YRDUA. The results showed that: (1) From 2005 to 2022, the per capita WREF (total water, agricultural water, and industrial water) of the YRDUA generally showed fluctuating declining trends, while the per capita WREF of domestic water and ecological water showed obvious growth. (2) The per capita WREF and the per capita WRECC were in the order of Jiangsu Province > Anhui Province > Shanghai City > Zhejiang Province. The spatial distribution of the per capita WREF was similar to those of the per capita WRECC, and most areas effectively consume water resources. (3) The explanatory power of the interaction between factors was greater than that of a single factor, indicating that the spatiotemporal variation in the per capita WREF of the YRDUA was affected by the combination of multiple factors and that there were regional differences in the major factors in the case of secondary metropolitan areas. (4) The per capita WREF of YRDUA was affected by natural resources, and the impact of the ecological condition on the per capita WREF increased gradually over time. The impact factors of secondary metropolitan areas also clearly changed over time. Our results showed that the ecological situation of per capita water resources in the YRDUA is generally good, with obvious spatial and temporal differences. Full article

The transition to smart, zero-carbon cities relies on advanced, sustainable energy solutions, with artificial intelligence (AI) playing a crucial role in optimizing renewable energy management. This study evaluates state-of-the-art AI models for solar power forecasting, emphasizing accuracy, reliability, and environmental sustainability. Using operational data from Benban Solar Park in Egypt and Sakaka Solar Power Plant in Saudi Arabia, two of the world’s largest solar installations, the research highlights the effectiveness of hybrid AI techniques. The hybrid Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) model outperformed other models, achieving a Mean Absolute Percentage Error (MAPE) of 2.04%, Root Mean Square Error (RMSE) of 184, Mean Absolute Error (MAE) of 252, and R² of 0.99 for Benban, and an MAPE of 2.00%, RMSE of 190, MAE of 255, and R² of 0.98 for Sakaka. This model excels at capturing complex spatiotemporal patterns in solar data while maintaining low computational CO₂ emissions, supporting sustainable AI practices. The findings demonstrate the potential of hybrid AI models to enhance the accuracy and sustainability of solar power forecasting, thereby contributing to efficient, resilient, and zero-carbon urban environments. This research provides valuable insights for policymakers and stakeholders aiming to advance smart energy infrastructure. Full article

Background: Disruptions in freight transportation—such as service delays, infrastructure failures, and labor strikes—pose significant challenges to the reliability and efficiency of intermodal networks. To address these challenges, this study introduces Adaptive Intermodal Transportation (AIT), a resilient and flexible planning framework that enhances Synchromodal Freight Transport (SFT) by integrating real-time disruption management. Methods: Building on recent advances, we propose two novel strategies: (1) Reassign with Delay Buffer, which enables dynamic rerouting of shipments within a user-defined delay tolerance, and (2) (De)Consolidation, which allows splitting or merging of shipments across services depending on available capacity. These strategies are incorporated into a re-planning module that complements a baseline optimization model and a continuous disruption-monitoring system. Numerical experiments conducted on a Great Lakes-based case study evaluate the performance of the proposed strategies against a benchmark approach. Results: Results show that under moderate and high-disruption conditions, the proposed strategies reduce delay and disruption-incurred costs while increasing the percentage of matched shipments. The Reassign with Delay Buffer strategy offers controlled flexibility, while (De)Consolidation improves resource utilization in constrained environments. Conclusions: Overall, the AIT framework demonstrates strong potential for improving operational resilience in intermodal freight systems by enabling adaptive, disruption-aware planning decisions. Full article

Accurate estimation of actual evapotranspiration (ET) is critical for understanding hydrothermal cycles and ecosystem functioning in arid regions, where water scarcity governs ecological resilience. To address persistent gaps in ET quantification, this study integrates multi-source remote sensing data, energy balance modeling, and ground-based validation that significantly enhances spatiotemporal ET accuracy in the vulnerable desert steppe ecosystems. The study utilized meteorological data from several national stations and Landsat-8 imagery to process monthly remote sensing images in 2019. The Surface Energy Balance System (SEBS) model, chosen for its ability to estimate ET over large areas, was applied to derive modeled daily ET values, which were validated by a large-weighted lysimeter. It was shown that ET varied seasonally, peaking in July at 6.40 mm/day, and reaching a minimum value in winter with 1.83 mm/day in December. ET was significantly higher in southern regions compared to central and northern areas. SEBS-derived ET showed strong agreement with lysimeter measurements, with a mean relative error of 4.30%, which also consistently outperformed MOD16A2 ET products in accuracy. This spatial heterogeneity was driven by greater vegetation coverage and enhanced precipitation in the southeast. The steppe ET showed a strong positive correlation with surface temperatures and vegetation density. Moreover, the precipitation gradients and land use were primary controllers of spatial ET patterns. The process-based SEBS frameworks demonstrate dual functionality as resource-optimized computational platforms while enabling multi-scale quantification of ET spatiotemporal heterogeneity; it was therefore a reliable tool for ecohydrological assessments in an arid steppe, providing critical insights for water resource management and drought monitoring. Full article

The intensification of anthropogenic pressures, particularly those related to agriculture driven by increasing demands for food and cash crops, generates negative environmental externalities. Assessing these externalities is essential to better identify and implement measures that promote the environmental sustainability of rural landscapes. This study aims to develop a multi-criteria assessment method of the negative environmental externalities of rural landscapes in the northern Benin agricultural basin, based on satellite-derived data. Starting from a 12-class land cover map produced through satellite image classification, the evaluation was conducted in three steps. First, the 12 land cover classes were reclassified into Human Disturbance Coefficients (HDCs) via a weighted sum model multi-criteria analysis based on nine criteria related to the negative environmental externalities of anthropogenic activities. Second, the HDC classes were spatially aggregated using a regular grid of 1 km² landscape cells to produce the Landscape Environmental Sustainability Index (LESI). Finally, various discretization methods were applied to the LESI for cartographic representation, enhancing spatial interpretation. Results indicate that most areas exhibit moderate environmental externalities (HDC and LESI values between 2.5 and 3.5), covering 63–75% (HDC) and 83–94% (LESI) of the respective sites. Areas of low environmental externalities (values between 1.5 and 2.5) account for 20–24% (HDC) and 5–13% (LESI). The LESI, derived from accessible and cost-effective satellite data, offers a scalable, reproducible, and spatially explicit tool for monitoring landscape sustainability. It holds potential for guiding territorial governance and supporting transitions towards more sustainable land management practices. Future improvements may include, among others, refining the evaluation criteria and introducing variable criteria weighting schemes depending on land cover or region. Full article

Understanding the migratory strategies of plateau-endemic species is essential for informing effective conservation, especially under climate change. The Black-necked Crane (Grus nigricollis), a high-altitude specialist, has shown notable population growth in recent years. We analysed satellite tracking data from 16 individuals of a western subpopulation in the lake basin region of northern Tibet (2021–2024), focusing on migration patterns, stopover use, and habitat selection. This subpopulation exhibited short-distance (mean: 284.21 km), intra-Tibet migrations with low reliance on stopover sites. Autumn migration was shorter, more direct, higher in altitude, and slower in speed than spring migration. Juveniles used smaller, more fragmented habitats than subadults, and their spatial range expanded over time. Given these patterns, we infer that the short-distance migration strategy may reduce energetic demands and mortality risks while increasing route flexibility—characteristics that may benefit population growth. We refer to this as a low-energy, high-efficiency migration strategy, which we hypothesise could support faster population growth and enhance resilience to environmental change. We recommend prioritizing the conservation of short-distance migration corridors, such as the typical lake basin area in northern Tibet–Yarlung Tsangpo River system, which may help sustain plateau-endemic migratory populations under future climate scenarios. Full article

To enhance the structural safety in wind-sand regions, this study employs the Euler-Lagrange numerical method to investigate the wind pressure characteristics of typical low-rise auxiliary buildings in a strong wind-blown sand environment. The results reveal that sand particle motion dissipates wind energy, leading to a slight reduction in average wind speed, while the increase in small-scale vortex energy enhances fluctuating wind speed. In the sand-laden wind field, the average wind pressure coefficient shows no significant change, whereas the fluctuating wind pressure coefficient increases markedly, particularly in the windward region of the building. Analysis of the skewness and kurtosis of wind pressure reveals that the non-Gaussian characteristics of wind pressure are amplified in the sand-laden wind, thereby elevating the risk of damage to the building envelope. Consequently, it is recommended that the design fluctuating wind load for envelopes and components of low-rise buildings in wind-sand regions be increased by 10% to enhance structural resilience. Full article

Urban public transportation systems face increasing pressure from shifting travel patterns, rising peak-hour demand, and the need for equitable and resilient service delivery. While complex network theory has been widely applied to analyze transit systems, limited attention has been paid to behavioral segmentation within such networks. This study introduces a frequency-based framework that differentiates high-frequency (HF) and low-frequency (LF) passengers to examine how distinct user groups shape network structure, congestion vulnerability, and robustness. Using over 20 million smart-card records from Beijing’s multimodal transit system, we construct and analyze directed weighted networks for HF and LF users, integrating topological metrics, temporal comparisons, and community detection. Results reveal that HF networks are densely connected but structurally fragile, exhibiting lower modularity and significantly greater efficiency loss during peak periods. In contrast, LF networks are more spatially dispersed yet resilient, maintaining stronger intracommunity stability. Peak-hour simulation shows a 70% drop in efficiency and a 99% decrease in clustering, with HF networks experiencing higher vulnerability. Based on these findings, we propose differentiated policy strategies for each user group and outline a future optimization framework constrained by budget and equity considerations. This study contributes a scalable, data-driven approach to integrating passenger behavior with network science, offering actionable insights for resilient and inclusive transit planning. Full article