Search Results (58,511)

Pro-environmental behaviour (PEB) and its factors are widely analysed in the scientific literature to better understand individuals’ decisions and behavioural patterns in the environmental context. PEB is essential for achieving the European Union’s (EU) climate and sustainability objectives; however, significant differences persist between Western and Eastern member states. The article aims to assess factors and identify differences that determine pro-environmental behaviour in the Western and Eastern European Union countries. Particular attention is paid to the role of subjective well-being (SWB) and demographic and structural factors in shaping different dimensions of PEB at the regional level. This study examines the factors of PEB across these two regions using data from the European Social Survey (ESS). The empirical analysis is based on the application of mixed methods, including regression analysis and cluster analysis, which allows for the identification of regional patterns of behaviour and country profiles. Grounded on mixed-method empirical analyses, the findings demonstrate that pro-environmental behaviour and climate responsibility are shaped by distinct motivational mechanisms that vary systematically across European regions. SWB plays a stronger internal motivational role in Eastern Europe, while education and gender dominate in Western Europe. This study contributes to sustainability research by providing a comparative, interregional perspective and emphasising the need for differentiated policy strategies that take into account regional differences in behavioural motivations and structural conditions. The results of this study can be applied in developing regionally adaptable environmental and climate policy measures focused on different behavioural motivation, which will increase policy effectiveness and public engagement in both Eastern and Western EU countries. Full article

Monitoring heritage landscapes is essential for evaluating long-term ecological integrity, mitigating environmental risks, and supporting sustainable heritage management. This study investigates land cover transformation and ecological environment quality in the Jingmai Mountain Cultural Landscape Heritage Area, a UNESCO World Heritage Site, using high-resolution satellite imagery from 2013 and 2023 and geospatial analysis tools (ENVI 5.3 and ArcGIS 10.8). Supervised classification using the maximum likelihood algorithm was employed to detect land use and land cover changes, and a quantitative ecological environment quality index based on land use areas and ecological coefficients was used to assess regional ecological quality. Land cover dynamics, heritage element shifts, and ecological quality variations before and after the site’s inscription were analyzed. The results indicate that core landscape structures remained relatively stable in both the construction control area and the core application zone. In the construction control area, land cover changes totaled 32.28 km², with the most significant transformations occurring in forested areas (36%), followed by cultivated lands (19%). In the application zone, total land cover change reached 10.99 km², primarily involving cultivated lands (33%) and built-up areas (27%). Ecological environment quality indices exhibited a slight positive trend, increasing from 0.4476 to 0.4512 in the construction control area and from 0.2449 to 0.2521 in the application zone between 2013 and 2023. This study provides a decade-long spatial assessment of land use transitions in a UNESCO cultural landscape and proposes a transferable framework for integrating ecological quality evaluation into heritage landscape monitoring. The findings offer evidence-based insights into heritage conservation and rural development planning and support the implementation of sustainable landscape management strategies aligned with national policies and the Sustainable Development Goals. Full article

Perinatal brain injury (PBI) is a leading cause of long-term neurological deficits in newborns, yet effective therapies are limited. At the cellular level, PBI involves hypoxic–ischemic stress, neuroinflammation, oxidative damage, excitotoxicity, and disrupted neurovascular and glial development. Traditional animal models and 2D cultures cannot fully capture the spatiotemporal complexity of the developing human brain, highlighting the need for more physiologically relevant systems. Human brain organoids have emerged as advanced three-dimensional models that recapitulate region-specific cytoarchitecture, neuronal and glial differentiation, and early circuit formation. They enable modeling of hypoxic–ischemic and inflammatory insults, allowing for the study of injury-induced changes in neurogenesis, gliogenesis, synaptic development, and cell interactions. Organoids facilitate identification of molecular pathways involved in injury and repair, supporting therapeutic target discovery. Using patient-derived induced pluripotent stem cells, organoids also allow personalized pharmacogenomic studies to assess genotype-dependent drug responses and toxicity. Despite limitations such as variability, lack of vascularization and immune components, and ethical considerations, brain organoids offer a promising platform to bridge developmental neurobiology and translational therapeutics, paving the way for targeted and individualized interventions in PBI. Full article

Regional production-consumption imbalances and deficient multimodal connectivity in grain circulation systems have rendered traditional segmented transport inefficient, loss-intensive, and costly, constraining overall supply chain performance. In China, the persistent north-to-south and west-to-east grain transfer patterns, driven by regional production–consumption imbalances, have imposed significant challenges on the grain circulation system, making multimodal transport optimization a critical priority for national food security. Multimodal transport, a critical logistics optimization strategy, integrates diverse transport modes and hub nodes to enable end-to-end coordination, thereby enhancing circulation efficiency and food security. This study systematically reviews the transport configurations and modal characteristics of grain multimodal transport, and employs bibliometric analysis with the VOSviewer tool to map publication trends and keyword co-occurrence networks. Subsequently, recent advances in transshipment hub location selection and route optimization in multimodal transport systems are examined. Finally, existing technical bottlenecks are summarized, and future research directions are outlined from the perspectives of intelligent logistics, green and low-carbon development, coordinated operations, and supply chain resilience. Full article

Forest fires are a major concern due to their significant impact on the environment, economy, and wildlife habitats. Efficient early detection systems can significantly mitigate their devastating effects. This paper provides a comprehensive review of forest fire detection (FFD) techniques and traces their evolution from basic lookout-based methods to sophisticated remote sensing technologies, including recent Internet of Things (IoT)- and Unmanned Aerial Vehicle (UAV)-based sensor network systems. Historical methods, characterized primarily by human surveillance and basic electronic sensors, laid the foundation for modern techniques. Recently, there has been a noticeable shift toward ground-based sensors, automated camera systems, aerial surveillance using drones and aircraft, and satellite imaging. Moreover, the rise of Artificial Intelligence (AI), Machine Learning (ML), and the IoT introduces a new era of advanced detection capabilities. These detection systems are being actively deployed in wildfire-prone regions, where early alerts have proven critical in minimizing damage and aiding rapid response. All FFD techniques follow a common path of data collection, pre-processing, data compression, transmission, and post-processing. Providing sufficient power to complete these tasks is also an important area of research. Recent research focuses on image compression techniques, data transmission, the application of ML and AI at edge nodes and servers, and the minimization of energy consumption, among other emerging directions. However, to build a sustainable FFD model, proper sensor deployment is essential. Sensors can be either fixed at specific geographic locations or attached to UAVs. In some cases, a combination of fixed and UAV-mounted sensors may be used. Careful planning of sensor deployment is essential for the success of the model. Moreover, ensuring adequate energy supply for both ground-based and UAV-based sensors is important. Replacing sensor batteries or recharging UAVs in remote areas is highly challenging, particularly in the absence of an operator. Hence, future FFD systems must prioritize not only detection accuracy but also long-term energy autonomy and strategic sensor placement. Integrating renewable energy sources, optimizing data processing, and ensuring minimal human intervention will be key to developing truly sustainable and scalable solutions. This review aims to guide researchers and developers in designing next-generation FFD systems aligned with practical field demands and environmental resilience. Full article

In many developing regions, the lack of a continuous cold chain poses a significant challenge for the preservation of table eggs. This study developed bioactive coatings based on citric pectin enriched with Cordia verbenacea DC aqueous extract to maintain egg quality under non-refrigerated conditions (25 days). A total of 144 fresh eggs were divided into a Control group and five treatment groups with increasing extract concentrations (0% to 100%). Quality was assessed through physical, chemical, and microbiological parameters, supported by principal component analysis (PCA) and random forest (RF) modeling. The results showed that all coated eggs maintained significantly higher Haugh units (classified as Grade B) compared to the control (grade C) (p < 0.05). The microbial load on the shell, a fundamental indicator of sanitary-hygienic conditions, was reduced from 70.0 ± 5.8 CFU/egg in the control to zero in the 100% extract treatment. The RF model achieved 97.06% accuracy in classifying the treatments, identifying microbial load and Haugh unit as the primary predictors of quality. This bioactive coating represents a sustainable and low-cost technology to enhance the shelf life and safety of eggs in markets without refrigeration infrastructure. Full article

Quantiles are among the most fundamental constructs in probability theory and statistics, intrinsically linked to order structures, stochastic dominance, and the principles of robust statistical inference. Although the univariate theory of quantiles is by now classical and well developed, their generalization to multivariate settings remains mathematically subtle and methodologically demanding. In particular, extending the notion of “location within a distribution” beyond one dimension raises delicate questions of geometry, ordering, and equivariance. Within this landscape, the spatial—or geometric—formulation of multivariate quantiles has emerged as a rigorous and conceptually unifying framework capable of reconciling these issues. In this work we advance this paradigm by introducing a kernel-based estimation procedure for nonparametric conditional geometric quantiles of a multivariate response $Y\in {\mathbb{R}}^q$ ($q\ge 2$) given a functional covariate X that takes values in an infinite-dimensional space. The data are assumed to form a strictly stationary and ergodic process, while the responses may be subject to a missing-at-random mechanism, a feature of substantial practical relevance. Our analysis establishes strong consistency of the proposed estimator, characterizes its optimal convergence rate, and derives its asymptotic distribution. These limit theorems, in turn, provide the theoretical foundation for constructing asymptotically valid confidence regions and for performing inference in multivariate quantile regression with functional covariates. The theoretical developments rest on natural complexity conditions for the involved functional classes together with mild smoothness and regularity assumptions. This balance between generality and mathematical precision ensures that the resulting methodology is not only robust in a rigorous probabilistic sense but also widely applicable to contemporary problems in high-dimensional and functional data analysis. The proposed methodology is numerically investigated through simulations and is implemented in a real data application. Full article

Complete records of fault activity are very valuable for assessing possible earthquakes. Fault scarps are one key to exploring past fault activity. Through the records of fault scarps, we can obtain evidence of fault activity and faulting events in paleoseismology. The Longshou Shan Mountains are located at the northeastern edge of the Tibetan Plateau. Here, through the measurement of fault scarps and the geomorphological analysis of alluvial fans and river beds, we have found that fault scarps here have experienced long earthquake cycles, and the propagation of the fault system has created the alluvial fan sequence. We provide evidence of active faults that ruptured the surface in Quaternary times and further deduce the regional landscape development process. Full article

To offer multi-edge type low-density parity-check (MET-LDPC) codes with better performance, this paper proposes a regional message scaling min-sum (RMS) decoding algorithm which improves the performance of the traditional min-sum (MS) decoding algorithm and its modified versions. The contributions of this study are as follows. First, based on the edge-type topology of MET-LDPC codes, we fully exploit their inherent structural information to develop a cross-region decoding architecture by dynamically partitioning the edges of the Tanner graph into three functional regions. Second, we introduce cross-region message scaling (CMS) factors to establish an asymmetric information flow control mechanism, which adaptively regulates the intensity of information exchange across regions. Third, by integrating the multi-edge structure, the cross-region decoding architecture, and the asymmetric information flow control mechanism into a unified framework, we propose the RMS decoding algorithm tailored for MET-LDPC codes. For various code lengths, simulation results demonstrate that the proposed algorithm achieves a significantly lower error floor compared to the traditional MS decoding algorithm and its modified versions over the additive white Gaussian noise (AWGN) channel. Full article

Saudi Arabia is experiencing interactions between ongoing urbanization, tourism growth, infrastructure projects in western regions along the Red Sea, and volcanic hazards. The area contains extensive monogenetic volcanic fields with hundreds of volcanoes formed during the Quaternary period. The large scale of the region often limits and fragments volcanological research, resulting in insufficient age and chemical data to understand the spatial and temporal development of many volcanic fields. Increased tourism has created a need for volcanic hazard assessments, particularly since some volcanic fields are considered possible tourist destinations. Harrat Lunayyir, in northwestern Saudi Arabia, is an example where such assessments have been conducted. Hazard assessments seek to provide information about potential future eruption types, locations, and impacts over timeframes relevant to urban planning and risk management. Due to rapid local development, these assessments may be required on short notice for specific small areas within larger volcanic fields, even when geological data are limited. This report presents a deterministic, scenario-based method for addressing such requests in the Lunayyir Volcanic Field. Results indicate a young Holocene eruption site characterized by a complex scoria cone associated with lava spattering, Strombolian, violent Strombolian activity and extensive transitional-type lava effusion. Full article

Here, we adopt an historical approach towards reviewing research since the 1970s on the seed-borne virus diseases of cool-season pulses caused by pea seed-borne mosaic virus (PSbMV) in Australia’s grain cropping regions. All relevant investigations concerning the principal cool-season pulse crops infected; field pea, lentil, faba bean, chickpea, and the minor ones, Lathyrus species, vetches and narbon bean, are covered. However, as the PSbMV field pea pathosystem is the most studied, this receives greatest emphasis. The review starts with brief background information, and by describing the disease symptoms caused and the advances in sample testing procedures. Next, findings from past PSbMV studies are covered in greater detail including transmission by aphids, contact and seeds; occurrence in crops and seed stocks; pathotypes and genetic diversity; host resistance; and phytosanitary, cultural and chemical control measures. What these studies found about PSbMV biology, epidemiology and control is emphasized by describing past glasshouse and field experimentation. Then, practical research outcomes identifying PSbMV’s epidemic drivers, forecasting its epidemics and devising an integrated disease management strategy are emphasized. Examples of images that illustrate past investigations and research outputs are provided. Finally, principal research achievements and priorities for future Australian PSbMV cool-season pulse research are highlighted. Full article

Construction of an ecological security pattern is crucial to achieve ecological security and socioeconomic sustainability. Climate change and human activities jointly impact ecological security, but the construction of existing ecological security frameworks primarily considers human activities while rarely accounting for the effects of climate change. The Dawen River basin ecological security pattern was developed with the objectives of improving ecological function, safeguarding ecological security, and promoting sustainable development. Habitat quality was selected as an ecosystem service function in this study, and the InVEST model was employed for assessment. Based on the framework of “ecological sources identification-ecological resistance surface establishment-ecological security pattern”, a new framework was developed by considering the effect of climate change on the establishment of ecological resistance. The results showed that: (1) a total of 34 ecological source areas were primarily distributed in Mount Tai, Mount Culai, Mount Xinfu and Dongping Lake regions; (2) a total of 42 ecological pinch points, 73 ecological barriers, and 76 ecological corridors were primarily distributed in the eastern part of the basin; and (3) an ecological security pattern characterized by “Two Belts and Four Zones” was constructed for the Dawen River basin, and corresponding protection strategies were proposed. The findings elucidate the impacts of climate change on ecological security pattern, offering valuable scientific insights for ESP development at basin scale. Full article

Sea-level rise (SLR) and coastal flooding are among the most pressing climate-related challenges facing coastal regions worldwide, and their impacts are further intensified by rapid urbanization. These processes pose serious socioeconomic and environmental risks, including increased flood exposure, threats to public health, and damage to critical infrastructure. In Saudi Arabia, more than 3100 km² of coastal land lies at elevations of 1 m or lower; however, reliable assessments of future sea-level rise and its potential impacts remain limited, creating significant uncertainty for long-term planning. This study addresses this knowledge gap by identifying areas vulnerable to sea-level rise and coastal flooding through the development of inundation maps for the Dammam Metropolitan Area (DMA) as a case study, while also outlining potential adaptation measures. Using satellite imagery and geospatial datasets, changes in the DMA shoreline between 2014 and 2024 were analyzed, and sea-level rise scenarios were simulated based on projections from the Intergovernmental Panel on Climate Change (IPCC). The results indicate that under a 0.6 m sea-level rise scenario, flooding would be limited to a small area of approximately 0.2 km² in the Half-Moon residential district. In contrast, a 1.1 m sea-level rise scenario reveals a substantial increase in risk, with nearly 83 km² of the DMA potentially exposed to coastal flooding. Based on these findings, targeted disaster management and adaptation strategies are recommended for areas most vulnerable to sea-level rise. The study highlights the need for policies regulating coastal reclamation and other climate-sensitive developments to minimize future flood risks. It supports the United Nations Sustainable Development Goals, particularly SDG 11 (Sustainable Cities and Communities) and SDG 13 (Climate Action) by enhancing urban flood risk assessment and improving understanding of climate-driven sea-level rise impacts. Full article

This study presents a SCAPS-1D-based numerical optimization of an organic ultraviolet (UV) photodetector employing an FTO/PTB7/Spiro-OMeTAD/Au device architecture. The novelty of this work lies in a simulation-guided, UV-specific optimization strategy that combines thickness engineering, controlled doping, and contact work-function tuning to achieve intrinsic spectral selectivity without external optical filters. We systematically optimize material and device parameters, including active layer thicknesses, donor and acceptor densities, and the metal electrode work function, to enhance responsivity, detectivity, and spectral performance. Simulations identify optimal thicknesses of 1200 nm for PTB7 and 1000 nm for Spiro-OMeTAD, with donor concentrations of 1 × 10²⁰ cm⁻³ and 1 × 10¹⁸ cm⁻³, respectively. A comparative contact analysis demonstrates that replacing aluminum with gold (Au) forms a near-ohmic back contact, leading to improved hole extraction and suppressed dark current due to favorable energy-level alignment. The optimized device achieves a peak external quantum efficiency of approximately 80% in the 300–400 nm ultraviolet range, with a responsivity up to 0.4 A/W. The UV selectivity originates from the absorption characteristics of PTB7 combined with suppressed long-wavelength charge collection, resulting in a negligible response in the visible–near-infrared region. These results confirm the device’s strong potential for high-sensitivity, solar-blind UV photodetection. By integrating practical material selection with physically consistent SCAPS-1D optoelectronic modeling, this work provides a robust design framework to guide the development of next-generation organic UV photodetectors for environmental sensing, biomedical diagnostics, and wearable optoelectronics. Full article

The rise of the digital economy necessitates a scientific framework for evaluating rural logistics capacity, a critical enabler of agricultural and rural modernization. This study conceptualizes “rural logistics capacity in the digital economy” and constructs an evaluation system comprising four primary and fourteen secondary indicators. Using provincial panel data from the China Statistical Yearbook (2012–2023) and the entropy-weighted fuzzy matter-element method, we systematically assess the spatiotemporal evolution of China’s rural logistics capacity and empirically examine its direct impact on rural economic resilience. The results show that: (1) Rural logistics capacity in China has improved overall but remains regionally uneven, with persistent bottlenecks in digital infrastructure and operational capabilities; (2) Rural logistics capacity significantly enhances rural economic resilience, with stronger effects observed in western regions and non-major grain-producing areas. These findings suggest that policymakers should adopt region-specific strategies, prioritize digital infrastructure development, promote logistics technology innovation, and strengthen mechanisms for talent cultivation and interregional coordination. Such measures are essential for comprehensively upgrading rural logistics capacity, reinforcing rural economic resilience, and fostering the sustainable development of rural logistics systems. Full article