Search Results (3,115)

This study investigates the concept of landscape services (LS), which integrate environmental and sociocultural dimensions of sustainable development. Recognizing landscapes as essential to daily life and well-being, the research aims to support sustainable spatial planning by analyzing both their potential and their actual use. The study has three main objectives: (1) to assess the potential of 16 selected landscape types to provide six key LS through expert evaluation; (2) to determine actual LS usage patterns among the local community (residents); and (3) to identify agreements and discrepancies between expert assessments and resident use. The services analyzed include providing space for daily activities; regulating spatial structure through diversity and compositional richness; enhancing physical and mental health; enabling passive and active recreation; supporting personal fulfillment; and fostering social interaction. Expert-based surveys and participatory mapping with residents were used to assess the provision and use of LS. The results indicate consistent evaluations for forest and historical urban landscapes (high potential and use) and mining and transportation landscapes (low potential and use). However, significant differences emerged for mountain LS, rated highly by experts but used minimally by residents. These insights highlight the importance of aligning expert planning with community needs to promote sustainable land use policies and reduce spatial conflicts. Full article

An indicator-based approach was implemented to assess the contributions of soils in supplying ecosystem services, providing a scalable tool for modeling the spatial heterogeneity of soil functions at regional and local scales. The method consisted of (i) the definition of soil-based ecosystem services (SESs), using available point data and thematic maps; (ii) the definition of appropriate SES indicators; (iii) the assessment and mapping of potential SESs provision for the Emilia-Romagna region (22.510 km²) in NE Italy. Depending on data availability and on the role played by terrain features and soil geography and its complexity, maps of basic soil characteristics (textural fractions, organic C content, and pH) covering the entire regional territory were produced at a 1 ha resolution using digital soil mapping techniques and geostatistical simulations to explicitly consider spatial variability. Soil physical properties such as bulk density, porosity, and hydraulic conductivity at saturation were derived using pedotransfer functions calibrated using local data and integrated with supplementary information such as land capability and remote sensing indices to derive the inputs for SES assessment. Eight SESs were mapped at 1:50,000 reference scale: buffering capacity, carbon sequestration, erosion control, food provision, biomass provision, water regulation, water storage, and habitat for soil biodiversity. The results are discussed and compared for the different pedolandscapes, identifying clear spatial patterns of soil functions and potential SES supply. Full article

Aquatic vegetation plays a crucial role in freshwater ecosystems by providing habitats, regulating water quality, and supporting biodiversity. This study aims to monitor and analyze the dynamics of aquatic vegetation in Chimaditida Shallow Lake, Greece, using Sentinel-2 satellite imagery, with validation from field measurements. Data processing was performed using Google Earth Engine and QGIS. The study focuses on discriminating and mapping two classes of aquatic surface conditions: areas covered with Floating and Emergent Aquatic Vegetation and open water, covering all seasons from 1 March 2024, to 28 February 2025. Spectral bands such as B04 (red), B08 (near infrared), B03 (green), and B11 (shortwave infrared) were used, along with indices like the Modified Normalized Difference Water Index and Normalized Difference Vegetation Index. The classification was enhanced using Otsu’s thresholding technique to distinguish accurately between Floating and Emergent Aquatic Vegetation and open water. Seasonal fluctuations were observed, with significant peaks in vegetation growth during the summer and autumn months, including a peak coverage of 2.08 km² on 9 September 2024 and a low of 0.00068 km² on 28 December 2024. These variations correspond to the seasonal growth patterns of Floating and Emergent Aquatic Vegetation, driven by temperature and nutrient availability. The study achieved a high overall classification accuracy of 89.31%, with producer accuracy for Floating and Emergent Aquatic Vegetation at 97.42% and user accuracy at 95.38%. Validation with Unmanned Aerial Vehicle-based aerial surveys showed a strong correlation (R² = 0.88) between satellite-derived and field data, underscoring the reliability of Sentinel-2 for aquatic vegetation monitoring. Findings highlight the potential of satellite-based remote sensing to monitor vegetation health and dynamics, offering valuable insights for the management and conservation of freshwater ecosystems. The results are particularly useful for governmental authorities and natural park administrations, enabling near-real-time monitoring to mitigate the impacts of overgrowth on water quality, biodiversity, and ecosystem services. This methodology provides a cost-effective alternative for long-term environmental monitoring, especially in regions where traditional methods are impractical or costly. Full article

Cloud computing offers a broad spectrum of services to users, particularly in multi-cloud environments where service-centric features are introduced to support users from multiple endpoints. To improve service availability and optimize the utilization of required services, cloud brokerage has been integrated into multi-cloud systems. The primary objective of a cloud broker is to ensure the quality and outcomes of services offered to customers. However, traditional cloud brokers face limitations in measuring service trust, ensuring validity, and anticipating future enhancements of services across different cloud platforms. To address these challenges, the proposed intelligent cloud broker integrates an intelligence mechanism that enhances decision-making within a multi-cloud environment. This broker performs a comprehensive validation and verification of service trustworthiness by analyzing various trust factors, including service response time, sustainability, suitability, accuracy, transparency, interoperability, availability, reliability, stability, cost, throughput, efficiency, and scalability. Customer feedback is also incorporated to assess these trust factors prior to service recommendation. The proposed model calculates service ranking (SR) values for available cloud services and dynamically includes newly introduced services during the validation process by mapping them with existing entries in the Service Collection Repository (SCR). Performance evaluation using the Google cluster-usage traces dataset demonstrates that the ICB outperforms existing approaches such as the Clustering-Based Trust Degree Computation (CBTDC) algorithm and the Service Context-Aware QoS Prediction and Recommendation (SCAQPR) model. Results confirm that the ICB significantly enhances the effectiveness and reliability of cloud service recommendations for users. Full article

Addressing the need for contact load detection in wind turbine main bearings during service, a roller contact load measurement method is proposed. An analytical model characterizes the contact load-to-inner bore strain mapping relationship. To overcome the inherent low sensitivity of direct bore strain measurement, bore-to-measurement-point sensitivity analysis was optimized. Multiple structurally optimized sensor brackets were designed to enhance strain measurement sensitivity, and their performance was comparatively evaluated via simulation. To mitigate sensitivity fluctuations caused by roller rotation phase variations, a strain–phase–load calculation method incorporating real-time phase compensation was developed and verified through simulation analysis. A dedicated roller contact load testing system was constructed and experimental validation was conducted. Results demonstrate 95% accuracy in contact load acquisition. This method accurately obtains roller contact loads in wind turbine main bearings, proving crucial for studying bearing mechanical behavior, predicting fatigue life, optimizing structural design, and enhancing reliability. Full article

Background/Objectives: Perceived coercion has been associated with significant negative outcomes, including service avoidance and psychological distress. Despite growing interest, no recent comprehensive review has mapped the full range of factors influencing this experience. This scoping review aimed to synthesize and present the state of knowledge on the factors associated with perceived coercion by adults receiving psychiatric care. Methods: Following the Joanna Briggs Institute methodology, a systematic search of five databases and grey literature was conducted for publications from 1990 to 2025 in English and French. A total of 143 sources were included and thematically analyzed. Consultation with experts and individuals with lived experience enriched the interpretation of findings. Results: Five categories of factors were identified: individual, clinical, relational, legal, and structural. Relational and legal factors were most consistently associated with perceived coercion, while individual and clinical factors showed inconsistent findings. Structural influences were underexamined but significantly shaped the experiences of the individuals receiving care. Conclusions: Perceived coercion arises from a complex dynamic of individual, relational, and systemic influences. Reducing coercion requires moving beyond individual-level factors to address structural conditions and policy frameworks. Future research should prioritize qualitative and intersectional approaches and amplify the voices of those most affected by coercive practices in psychiatric care. Full article

Background: Pharmacy technicians are increasingly involved in immunization services, enhancing vaccine accessibility and reducing pharmacies’ workload. This scoping review aims to (1) provide a comprehensive overview of pharmacy technicians’ involvement in immunization services across various healthcare settings and countries, and (2) conduct a comparative analysis of training curricula for pharmacy technicians on immunization. Methods: A scoping review was conducted following the Arksey and O’Malley framework. A comprehensive search of the PubMed and Scopus databases was performed using keywords and MeSH terms such as “pharmacy technician(s)”, “immunization”, “vaccination”, “role”, and “involvement”. Studies included assessed pharmacy technicians’ roles in vaccine administration, training, and public health outcomes. Descriptive and thematic analyses were used to synthesize the findings. In addition, a supplementary analysis of immunization training curricula was conducted, reviewing programs from different countries to identify similarities, differences, and gaps in course structure, content, and delivery formats. Lastly, a comprehensive toolkit was developed, offering guidelines intended to facilitate the implementation of immunization training programs. Results: A total of 35 articles met the inclusion criteria, primarily from the United States of America (n = 30), Canada (n = 2), Ethiopia (n = 1), Denmark (n = 1) and United Kingdom (n = 1). The findings indicate that pharmacy technicians contribute significantly to vaccine administration, patient education, and workflow optimization, particularly in community pharmacies. The COVID-19 pandemic accelerated their involvement in immunization programs. Key challenges include regulatory barriers, a lack of standardized training, and resistance from other healthcare professionals. Facilitators include legislative support (e.g., the PREP Act), structured training programs, and collaborative pharmacist–technician models. Conclusions: Pharmacy technicians can play a vital role in expanding immunization services, improving vaccine uptake, and reducing pharmacist workload. Addressing regulatory inconsistencies, enhancing training, and fostering interprofessional collaboration are crucial for their effective integration of immunization programs. Since immunization by pharmacy technicians is not yet allowed in many EU countries, this review will provide a foundational basis to address their potential to support the healthcare workforce and improve access to immunization services. Full article

In Taiwan, hydro-meteorological data are fragmented across multiple agencies, limiting the effectiveness of coordinated flood response. To address this challenge and the increasing uncertainty associated with extreme rainfall, a real-time disaster prevention platform has been developed. This system integrates multi-source data and geospatial information through a cluster-based architecture to enhance pluvial flood management. Built on a Service-Oriented Architecture (SOA) and incorporating Internet of Things (IoT) technologies, AI-based convolutional neural networks (CNNs), and 3D drone mapping, the platform enables automated alerts by linking sensor thresholds with real-time environmental data, facilitating synchronized operational responses. Deployed in New Taipei City over the past three years, the system has demonstrably reduced flood risk during severe rainfall events. Region-specific action thresholds and adaptive strategies are continually refined through feedback mechanisms, while integrated spatial and hydrological trend analyses extend the lead time available for emergency response. Full article

The construction and maintenance of an ecological security pattern (ESP) are important for promoting the regional development of ecological civilizations, realizing sustainable and healthy development, and creating a harmonious and beautiful space for human beings and nature to thrive. Traditional construction methods have the limitations of a single dimension, a single method, and excessive human subjective intervention for source and corridor identification, without considering the multidimensional quality of the sources and the structural connectivity and resilience optimization of the corridors. Therefore, an ecological civilization demonstration area (Jiangxi Province) was used as the study area, a new research method for ESP was proposed, and an empirical study was conducted. To evaluate ecosystem service (ES) importance–disturbance–risk and extract sustainability sources through the deep embedded clustering–self-organizing map (DEC–SOM) deep unsupervised learning clustering algorithm, ecological networks (ENs) were constructed by applying the minimum cumulative resistance (MCR) gravity model and circuit theory. The ENs were then optimized to improve performance by combining the comparative advantages of the two approaches in terms of structural connectivity and resilience. A comparative analysis of EN performance was constructed among different functional control zones, and the ESP was constructed to include 42 ecological sources, 134 corridors, 210 restoration nodes, and 280 protection nodes. An ESP of ‘1 nucleus, 3 belts, 6 zones, and multiple corridors’ was constructed, and the key restoration components and protection functions were clarified. This study offers a valuable reference for ecological management, protection, and restoration and provides insights into the promotion of harmonious symbiosis between human beings and nature and sustainable regional development. Full article

This study focuses on the current service/care difficulties and challenges that social institutions in Hungary are facing during their daily operations; how they can react to them utilizing their internal resources, mechanisms, and capacities; and what concrete, tangible needs and demands are emerging in terms of methodological professional support, potential forms, interventions, and direction for professional development. A total of 24 general and 55 specific service and operational problems were identified and assessed in eight different service areas (family and child welfare services, family and child welfare centers, respite care for children, care for the homeless, addiction intervention, care for people with disabilities, care for psychiatric patients, specialized care for the elderly, and basic services for the elderly). The empirical base of the study uses a database of 201 online questionnaires completed by a professional target group working for social service providers in two counties (Győr-Moson-Sopron and Veszprém), representing 166 social service providers. The questionnaires were completed between November and December of 2022. The findings will be used to develop a professional support and development problem map. Social institutions face complex and serious service/care difficulties and challenges in their daily operations. Three distinctive basic problems clearly stand out in both severity and significance from the complex set of factors assessed. The biggest problem in the social care system is clearly the complex challenge of low wages, followed by the administrative burdens in the ranking of operational difficulties, and the third key factor was the psycho-mental workload of staff. Full article

Background: International migration is a growing global phenomenon involving diverse groups, such as labor migrants, international marriage migrants, refugees, and international students. International migrants face unique mental health challenges influenced by adversities such as social isolation and limited access to mental health services. This study employs bibliometric methods to systematically analyze the global body of literature on international migrants’ mental health. Methods: The literature on the mental health of international migrants published until October 2024 was searched using the Web of Science database. The search terms included (‘International migrants’ OR ‘migrant workers’ OR ‘international students’ OR ‘refugees’ OR ‘asylum seekers’ OR ‘smuggled migrants’) AND ‘mental health’. VOSviewer was used to conduct bibliometric analysis, focusing on co-authorship patterns, keyword co-occurrence, and citation networks. Results: Over the past four decades, research on the mental health of international migrants has grown substantially, with major migration destinations such as the United States, Europe, and Australia playing prominent roles in this field. ‘Post-traumatic stress disorder (PTSD)’ was the most frequent keyword in publications, with strong links to ‘trauma’ and ‘depression’. In recent years, with the impact of global socioenvironmental changes and emergencies such as the COVID-19 pandemic, the research focus has gradually shifted towards social support, service accessibility, and cultural adaptation. Conclusions: International migration is a far-reaching global phenomenon, and addressing the mental health of migrant populations is essential for advancing public health, social cohesion, and sustainable development. This study provides the first bibliometric overview of research in this domain, mapping its thematic evolution and collaborative structure. The findings offer valuable insights into the field’s development and may support future interdisciplinary collaboration and the formulation of culturally informed, evidence-based approaches in migrant mental health. Full article

The large-scale integration of stochastic renewable energy sources necessitates enhanced dynamic balancing capabilities in power systems, positioning hydropower as a critical balancing asset. Conventional excitation systems utilizing hot-standby dual-redundancy configurations remain susceptible to unit shutdown events caused by regulator failures. To mitigate this vulnerability, this study proposes a peer-to-peer distributed excitation architecture integrating asynchronous traffic shaping (ATS) and Data Distribution Service (DDS) technologies. This architecture utilizes control channels of equal priority and achieves high redundancy through cross-communication between discrete acquisition and computation modules. This research advances three key contributions: (1) design of a peer-to-peer distributed architectural framework; (2) development of a real-time data interaction methodology combining ATS and DDS, incorporating cross-layer parameter mapping, multi-priority queue scheduling, and congestion control mechanisms; (3) experimental validation of system reliability and redundancy through dynamic simulation. The results confirm the architecture’s operational efficacy, delivering both theoretical foundations and practical frameworks for highly reliable excitation systems. Full article

This study presents a computational analysis of industry-specific advertising message strategies through the theoretical lens of the FCB (Foote, Cone & Belding) grid framework. Leveraging the AiSAC (AI Analysis System for Ad Creation) system developed by the Korea Broadcast Advertising Corporation (KOBACO), we analyzed 27,000 Korean advertisements across five major industries using advanced machine learning techniques. Through Latent Dirichlet Allocation topic modeling with a coherence score of 0.78, we identified five distinct message strategies: emotional appeal, product features, visual techniques, setting and objects, and entertainment and promotion. Our computational analysis revealed that each industry exhibits a unique “message strategy fingerprint” that significantly discriminates between categories, with discriminant analysis achieving 62.7% classification accuracy. Time-series analysis using recurrent neural networks demonstrated a significant evolution in strategy preferences, with emotional appeal increasing by 44.3% over the study period (2015–2024). By mapping these empirical findings onto the FCB grid, the present study validated that industry positioning within the grid’s quadrants aligns with theoretical expectations: high-involvement/think (IT and Telecom), high-involvement/feel (Public Institutions), low-involvement/think (Food and Household Goods), and low-involvement/feel (Services). This study contributes to media science by demonstrating how computational methods can empirically validate the established theoretical frameworks in advertising, providing a data-driven approach to understanding message strategy patterns across industries. Full article

The growing mismatch between ecosystem service (ES) supply and demand underscores the importance of thoroughly understanding their spatiotemporal patterns and key drivers to promote ecological civilization and sustainable development at the regional level in China. This study investigates six key ES indicators across mainland China—habitat quality (HQ), carbon sequestration (CS), water yield (WY), sediment delivery ratio (SDR), food production (FP), and nutrient delivery ratio (NDR)—by integrating a suite of analytical approaches. These include a spatiotemporal analysis of trade-offs and synergies in supply, demand, and their ratios; self-organizing maps (SOM) for bundle identification; and interpretable machine learning models. While prior research studies have typically examined ES at a single spatial scale, focusing on supply-side bundles or associated drivers, they have often overlooked demand dynamics and cross-scale interactions. In contrast, this study integrates SOM and SHAP-based machine learning into a dual-scale framework (grid and city levels), enabling more precise identification of scale-dependent drivers and a deeper understanding of the complex interrelationships between ES supply, demand, and their spatial mismatches. The results reveal pronounced spatiotemporal heterogeneity in ES supply and demand at both grid and city scales. Overall, the supply services display a spatial pattern of higher values in the east and south, and lower values in the west and north. High-value areas for multiple demand services are concentrated in the densely populated eastern regions. The grid scale better captures spatial clustering, enhancing the detection of trade-offs and synergies. For instance, the correlation between HQ and NDR supply increased from 0.62 (grid scale) to 0.92 (city scale), while the correlation between HQ and SDR demand decreased from −0.03 to −0.58, indicating that upscaling may highlight broader synergistic or conflicting trends missed at finer resolutions. In the spatiotemporal interaction network of supply–demand ratios, CS, WY, FP, and NDR persistently show low values (below −0.5) in western and northern regions, indicating ongoing mismatches and uneven development. Driver analysis demonstrates scale-dependent effects: at the grid scale, HQ and FP are predominantly influenced by socioeconomic factors, SDR and WY by ecological variables, and CS and NDR by climatic conditions. At the city level, socioeconomic drivers dominate most services. Based on these findings, nine distinct supply–demand bundles were identified at both scales. The largest bundle at the grid scale (B3) occupies 29.1% of the study area, while the largest city-scale bundle (B8) covers 26.5%. This study deepens the understanding of trade-offs, synergies, and driving mechanisms of ecosystem services across multiple spatial scales; reveals scale-sensitive patterns of spatial mismatch; and provides scientific support for tiered ecological compensation, integrated regional planning, and sustainable development strategies. Full article

This paper proposes a GNSS-compatible method for characterizing the motion of UAV-based navigation enhancement platforms, designed to provide reliable navigation and positioning services in emergency scenarios where GNSS signals are unavailable or severely degraded. The method maps UAV trajectories into standard GNSS navigation messages by establishing a correspondence between ephemeris parameters and platform positions through coordinate transformation and Taylor series expansion. To address modeling inaccuracies, the approach incorporates truncation error analysis and motion-assumption compensation via parameter optimization. This design enables UAV-mounted pseudolite systems to broadcast GNSS-compatible signals without modifying existing receivers, significantly enhancing rapid deployment capabilities in complex or degraded environments. Simulation results confirm precise positional representation in static scenarios and robust error control under dynamic motion through higher-order modeling and optimized broadcast strategies. UAV flight tests demonstrated a theoretical maximum error of 0.4262 m and an actual maximum error of 3.1878 m under real-world disturbances, which is within operational limits. Additional experiments confirmed successful message parsing with standard GNSS receivers. The proposed method offers a lightweight, interoperable solution for integrating UAV platforms into GNSS-enhanced positioning systems, supporting timely and accurate navigation services in emergency and disaster relief operations. Full article