Search Results (22,326)

Ultra-wideband (UWB) technology is a crucial facilitator for high-data-rate wireless communication due to its extensive frequency spectrum and low power consumption. Simultaneously, multiple-input multiple-output (MIMO) systems have garnered considerable attention owing to their capability to enhance channel capacity and link dependability. This article discusses the development of small, high-performance MIMO UWB antennas with mutual suppression capabilities to fully use the benefits of both technologies. Additionally, the suggested antenna features a straightforward design and dual-band-notched characteristics. The antenna structure includes two radiating elements measuring 85 × 45 mm². These elements use a rectangular patch provided by a coplanar waveguide (CPW). Double U-shaped slots are incorporated into the rectangular patch to introduce dual-band-notched properties, which help mitigate interference from WiMAX and WLAN communication systems. The antenna is fabricated on a Mylar^® polyester film substrate of 0.3 mm in thickness, with a dielectric constant of 3.2. According to the measurement results, the suggested antenna functions efficiently across the frequency spectrum of 2.29 to 20 GHz, with excellent impedance matching throughout the bandwidth. Furthermore, it provides dual-band-notched coverage at 3.08–3.8 GHz for WiMAX and 4.98–5.89 GHz for WLAN. The antenna exhibits impressive performance, including favorable radiation attributes, consistent gain, and little mutual coupling (less than −20 dB). Additionally, the envelope correlation coefficient (ECC) is extremely low (ECC < 0.01) across the working bandwidth, which indicates excellent UWB MIMO performance. This paper offers an appropriate design methodology for future flexible and compact UWB MIMO systems that can serve as interference-resilient antennas for next-generation wireless applications. Full article

Chlorophyll biosynthesis is essential for photosynthesis and plant development. Disruptions in this pathway often manifest as pigment-deficient phenotypes. This study characterizes the morphological, anatomical, and physiological consequences of a chlorophyll-deficient rice mutant (yellow seedling, YS) caused by a loss-of-function mutation in the OsCHLI gene, which encodes the ATPase subunit of magnesium chelatase. Comparative analyses between YSs and wild-type green seedlings (GSs) revealed that YSs exhibited severe growth retardation, altered mesophyll structure, reduced xylem and bulliform cell areas, and higher stomatal and papillae density. These phenotypes were strongly light-dependent, indicating that OsCHLI plays a crucial role in light-mediated chloroplast development and growth. Transcriptome analysis further revealed global down-regulation of photosynthesis-, TCA cycle-, and cell wall-related genes, alongside selective up-regulation of redox-related pathways. These results suggest that chlorophyll deficiency induces systemic metabolic reprogramming, prioritizing stress responses over growth. This study highlights the multifaceted role of OsCHLI in plastid maturation, retrograde signaling, and developmental regulation, providing new insights for improving photosynthetic efficiency and stress resilience in rice. Full article

Hydrogels are water-rich polymeric networks mimicking the body’s extracellular matrix, making them highly biocompatible and ideal for precision medicine. Their “tunable” and “smart” properties enable the precise adjustment of mechanical, chemical, and physical characteristics, allowing responses to specific stimuli such as pH or temperature. These versatile materials offer significant advantages over traditional drug delivery by facilitating targeted, localized, and on-demand therapies. Applications range from diagnostics and wound healing to tissue engineering and, notably, cancer therapy, where they deliver anti-cancer agents directly to tumors, minimizing systemic toxicity. Hydrogels’ design involves careful material selection and crosslinking techniques, which dictate properties like swelling, degradation, and porosity—all crucial for their effectiveness. The development of self-healing, tough, and bio-functional hydrogels represents a significant step forward, promising advanced biomaterials that can actively sense, react to, and engage in complex biological processes for a tailored therapeutic approach. Beyond their mechanical resilience and adaptability, these hydrogels open avenues for next-generation therapies, such as dynamic wound dressings that adapt to healing stages, injectable scaffolds that remodel with growing tissue, or smart drug delivery systems that respond to real-time biochemical cues. Full article

Device-free localization and tracking (DFLT) has emerged as a promising technique for location-aware Internet-of-Things (IoT) applications. However, most existing DFLT systems based on narrowband sensing networks suffer from reduced accuracy in indoor environments due to the susceptibility of received signal strength (RSS) measurements to multipath interference. In this paper, we propose a real-time DFLT system leveraging ultra-wideband (UWB) sensors. The system estimates target-induced shadowing using two UWB RSS measurements, which are shown to be more resilient to multipath effects compared to their narrowband counterparts. To enable real-time tracking, we further design an efficient measurement protocol tailored for UWB networks. Field experiments conducted in both indoor and outdoor environments demonstrate that our UWB-based system significantly outperforms its traditional narrowband DFLT solutions in terms of accuracy and robustness. Full article

This paper presents the SMALLDERS project, a European initiative aimed at transforming smallholders’ business models through an innovative technological platform. The platform functions as an e-marketplace that connects small farmers directly with consumers while simultaneously promoting environmental sustainability and collaboration across the agri-food value chain. The study evaluates the platform’s commercial viability and acceptance through a mixed-methods approach, incorporating qualitative and quantitative data. Research methods include focus group sessions, interviews with key stakeholders—such as transport companies, large distributors, and public administrations—and a consumer survey assessing intentions and attitudes toward the e-marketplace. Results indicate limited overall consumer readiness to adopt the platform; however, 48.6% of respondents expressed willingness to use it provided competitive prices and personal benefits are assured. Smallholders regard e-commerce as a promising opportunity, yet they face significant barriers, including limited resources, low digital literacy, and logistical constraints. Stakeholders generally view the platform positively, emphasizing that its success depends on achieving a critical mass of business volume. To foster adoption, SMALLDERS proposes three business models for smallholders: sustainable, cooperative, and technological. The platform includes a user-friendly feature to assist smallholders in transitioning among these models, complemented by training and support services designed to encourage more resilient and innovative agricultural practices. Full article

This paper explores how blockchain technology, widely known as the backbone of cryptocurrencies, can be harnessed to address limitations of traditional water quality monitoring (WQM) systems. Blockchain offers a decentralized, tamper-proof ledger that enables secure, transparent, and traceable data management across distributed networks. When applied to water quality monitoring, blockchain facilitates real-time data acquisition, enhances data integrity, and enables smart contracts for automated regulatory compliance and alerts. These features not only improve the accuracy and efficiency of WQM systems but also build public trust in the reported data. Key insights from current research and pilot applications highlight blockchain’s capacity to integrate with IoT devices for real-time sensing, support adaptive water governance, and empower local stakeholders through decentralized control and transparent access to information. The implications for policy and practice are significant: blockchain-based WQM can support stronger regulatory enforcement, encourage cross-sector collaboration, and provide a robust digital foundation for sustainable water management in smart cities and rural areas alike. As such, this review paper positions blockchain as a transformative tool in the digital transition toward more resilient and equitable water management systems. Full article

Understanding how congestion forms and propagates over space and time is essential for improving the operational efficiency of urban traffic systems. Recent developments in causal emergence theory indicate that the causal structures underlying dynamic models are scale-dependent. Most existing studies on traffic congestion evolution focus on a single, fixed scale, which risks overlooking clearer causal patterns at other scales and thus limiting predictive power and practical applicability. To address this, we develop a multiscale congestion evolution modeling framework grounded in causal emergence theory. Within this framework we build dynamical models at multiple spatiotemporal scales using dynamic Bayesian networks (DBNs) and quantify the causal strength of these models using effective information (EI) and singular value decomposition (SVD)-based diagnostics. Using road networks from three central Kunshan regions, we validate the proposed framework across 24 spatiotemporal scales and five demand scenarios. Across all three regions and the tested scales, we observe evidence of causal emergence in congestion evolution dynamics. When results are pooled across regions and scenarios, models built at the 10 min/150 m scale exhibit stronger and more coherent causal structure than models at other scales. These findings demonstrate that the proposed framework can identify and help build dynamical models of congestion evolution at appropriate spatiotemporal scales, thereby supporting the development of proactive traffic management and effective resilience enhancement strategies for urban transport systems. Full article

Digital city planning increasingly relies on data-driven approaches to address complex urban sustainability challenges through innovative network analysis methodologies. This study introduces a comprehensive spatiotemporal network framework to examine digital innovation networks as fundamental infrastructure for urban sustainable development, focusing on the Yellow River Basin as a representative case study. Utilizing digital patent data as innovation indicators across 57 urban centers, we employ advanced network analysis techniques including Social Network Analysis (SNA) and the Quadratic Assignment Procedure (QAP) to investigate the spatiotemporal evolution patterns and underlying driving mechanisms of regional digital innovation networks. The methodology integrates big data analytics with urban planning applications to provide evidence-based insights for digital city planning strategies. Our empirical findings reveal three critical dimensions of urban sustainable development through digital innovation networks: First, the region demonstrated significant enhancement in digital innovation capacity from 2012 to 2022, with accelerated growth patterns post 2020, indicating robust urban resilience and adaptive capacity for sustainable transformation. Second, the spatial network configuration exhibited increasing interconnectivity characterized by strengthened urban–rural linkages and enhanced cross-regional innovation flows, forming a hierarchical centrality pattern where major metropolitan centers (Xi’an, Zhengzhou, Jinan, and Lanzhou) serve as innovation hubs driving coordinated regional development. Third, analysis of network formation mechanisms indicates that spatial proximity, market dynamics, and industrial foundations negatively correlate with network density, suggesting that regional heterogeneity in these characteristics promotes innovation diffusion and strengthens inter-urban connections, while technical human capital and governmental interventions show limited influence on network evolution. This research contributes to the digital city planning literature by demonstrating how data-driven network analysis can inform sustainable urban development strategies, providing valuable insights for policymakers and urban planners implementing AI technologies and big data applications in regional development planning. Full article

With the continuous expansion of power grids and the advancement of ultra-high voltage (UHV) projects, transmission lines are increasingly traversing areas characterized by micro-terrain. These localized topographic features can intensify meteorological effects, thereby increasing the risks of hazards such as conductor icing and galloping, directly threatening operational stability. Enhancing the disaster resilience of transmission lines in such environments requires accurate and efficient terrain identification. However, conventional recognition methods often neglect the spatial alignment of the transmission lines, limiting their effectiveness. This paper proposes a deep learning-based recognition framework that incorporates a dual-branch network architecture and a cross-branch spatial attention mechanism to address this limitation. The model explicitly captures the spatial correlation between transmission lines and surrounding terrain by utilizing line alignment information to guide attention along the line corridor. A semi-synthetic dataset, comprising 6495 simulated samples and 130 real-world samples, was constructed to facilitate model training and evaluation. Experimental results show that the proposed model achieves classification accuracies of 94.6% on the validation set and 92.8% on real-world test cases, significantly outperforming conventional baseline methods. These findings demonstrate that explicitly modeling the spatial relationship between transmission lines and terrain features substantially improves recognition accuracy, offering important support for hazard prevention and resilience enhancement in UHV transmission systems. Full article

This paper is aimed at landscape managers and designers. It looks at 123 real-world coastal landscape projects and organizes them into clear design categories, i.e., wetland restoration, hybrid infrastructure, or urban green spaces. We looked at how these projects were framed (whether they focused on climate adaptation, flood protection, or other goals) and how they tracked performance. We are hoping to bring some clarity to a very scattered field, helping us to see patterns in what is actually being carried out in terms of landscape interventions and increasing sea levels. We are hoping to provide a practical reference for making better, more climate-responsive design decisions. Coastal cities face escalating climate-driven threats from increasing sea levels and storm surges to urban heat islands. These threats are driving increased interest in nature-based solutions (NbSs) as green adaptive alternatives to traditional gray infrastructure. Despite an abundance of individual case studies, there have been few systematic syntheses aimed at landscape designers and managers linking design typologies, project framing, and performance outcomes. This study addresses this gap through a meta-synthesis of 123 implemented coastal landscape interventions aimed directly at landscape-oriented research and professions. Flood risk reduction was the dominant framing strategy (30.9%), followed by climate resilience (24.4%). Critical evidence gaps emerged—only 1.6% employed integrated monitoring approaches, 30.1% provided ambiguous performance documentation, and mean monitoring quality scored 0.89 out of 5.0. While 95.9% of the projects acknowledged SLR as a driver, only 4.1% explicitly integrated climate projections into design parameters. Community monitoring approaches demonstrated significantly higher ecosystem service integration, particularly cultural services (36.4% vs. 6.9%, $p<0.001$), and enhanced monitoring quality (mean score 1.64 vs. 0.76, $p<0.001$). Implementation barriers spanned technical constraints, institutional fragmentation, and data limitations, each affecting 20.3% of projects. Geographic analysis revealed evidence generation inequities, with systematic underrepresentation of high-risk regions (Africa: 4.1%; Latin America: 2.4%) versus concentration in well-resourced areas (North America: 27.6%; Europe: 17.1%). Full article

Pulque, an available traditional Mexican fermented beverage, has deep ethnographic and cultural significance. It was originally consumed by pre-Columbian civilizations, including the Teotihuacanos, Mexicas, Otomies, Zapotecas, Mixtecas, and Maya. It was revered as a sacred drink with both ceremonial and medicinal uses, often reserved for elites and priests. Its production is based on the ancestral extraction and fermentation of aguamiel, a sweet sap obtained from agave plants. While advances in food technology have occurred, traditional techniques for obtaining and fermenting aguamiel remain prevalent, especially in rural communities, reflecting the resilience of indigenous knowledge systems. Recent interest in pulque has focused on its nutritional content and potential health benefits when consumed in moderation, though risks related to excessive intake remain a concern. Moreover, cultural initiatives aim to revitalize indigenous heritage through gastronomic promotion, tourism routes, and festive traditions. This study explores pulque’s production processes, its cultural symbolism, and its evolving role within Mexican society, suggesting that its survival reflects both continuity and adaptation in the face of modernity. This paper is also presented as a narrative integrative review to explore the biocultural significance of pulque across the anthropological, historical, biochemical, and public-health domains. Full article

The registration system reform (RSR) represents a landmark innovation in China’s IPO system, aiming to promote a more transparent, competitive, and sustainable market. Exploiting the staggered implementation of RSR as a quasi-natural experiment, we employ a difference-in-differences (DID) model using a sample of Chinese A-share IPO firms from 2016 to 2022 to investigate its impact on corporate sustainability, as proxied by environmental, social, and governance (ESG) performance. Our findings indicate that RSR significantly enhances corporate ESG performance, especially the governance (G) performance. Mechanism analysis suggests that market competition, investor rationality, and sponsor reputation are potential channels through which the reform facilitates corporate sustainability. Furthermore, the above relationship is more pronounced in regions with a higher degree of marketization, among non-state-owned enterprises, and those with weaker profitability. Moreover, the reform not only exhibits long-term effects but also demonstrates positive spillover effects on peer firms originally listed under the approval-based system. Overall, our study extends the understanding of how capital market institutional reforms promote corporate sustainability in the era of the digital economy and provides valuable insights for regulators to standardize and enhance RSR, thereby establishing a resilient and sustainable financial ecosystem. Full article

As contemporary society and the global economy become increasingly dependent on satellite-based systems, the need for reliable and resilient positioning, navigation, and timing (PNT) services has never been more critical. This study investigates the impact of the geomagnetic storm that occurred in May 2024 on the performance of global navigation satellite system (GNSS) low-cost permanent stations. The research evaluates the influence of ionospheric disturbances on both positioning performance and raw GNSS observations. Two days were analyzed: 8 May 2024 (DOY 129), representing quiet ionospheric conditions, and 11 May 2024 (DOY 132), coinciding with the peak of the geomagnetic storm. Precise Point Positioning (PPP) and static relative positioning techniques were applied to data from a low-cost GNSS station (DYVA), supported by comparative analysis using a nearby geodetic-grade station (TRDS00NOR). The results showed that while RMS positioning errors remained relatively stable over 24 h, the maximum errors increased significantly during the storm, with the 3D positioning error nearly doubling on DOY 132. Short-term analysis revealed even larger disturbances, particularly in the vertical component, which reached up to 3.39 m. Relative positioning analysis confirmed the vulnerability of single-frequency (L1) solutions to ionospheric disturbances, whereas dual-frequency (L1+L2) configurations substantially mitigated errors, highlighting the effectiveness of ionosphere-free combinations during storm events. In the second phase, raw GNSS observation quality was assessed using detrended GPS L1 carrier-phase residuals and signal strength metrics. The analysis revealed increased phase instability and signal degradation on DOY 132, with visible cycle slips occurring between epochs 19 and 21. Furthermore, the average signal-to-noise ratio (SNR) decreased by approximately 13% for satellites in the northwest sky sector, and a 5% rise in total cycle slips was recorded compared with the quiet day. These indicators confirm the elevated measurement noise and signal disruption associated with geomagnetic activity. These findings provide a quantitative assessment of low-cost GNSS receiver performance under geomagnetic storm conditions. This study emphasizes their utility for densifying GNSS infrastructure, particularly in regions lacking access to geodetic-grade equipment, while also outlining the challenges posed by space weather. Full article

Coastal erosion and shoreline change represent major challenges for the sustainable management of coastal environments, with implications for infrastructure, ecosystems, biodiversity, and the socio-economic well-being of coastal communities. This study investigates the shoreline evolution of 79 Mediterranean microtidal beaches located along the southern coast of Sardinia Island (Italy), using the Digital Shoreline Analysis System (DSAS). Shorelines were manually digitised from high-resolution aerial orthophotos made available through the WMS service of the Autonomous Region of Sardinia, covering the period 1954–2022. Shoreline changes were assessed through five statistical indicators: Shoreline Change Envelope (SCE), Net Shoreline Movement (NSM), End Point Rate (EPR), Weighted Linear Regression (WLR), and Linear Regression Rate (LRR). The results highlight marked spatial and temporal variability in shoreline retreat and accretion, revealing patterns that link shoreline dynamics to the degree of anthropisation or naturalness of each beach. In fact, coastal areas characterised by local anthropogenic factors showed higher rates of shoreline retreat and/or accretion, while natural beaches showed greater stability and resilience in the long term. The outcomes of this analysis provide valuable insights into local coastal dynamics and represent a critical knowledge base for developing targeted adaptation strategies, supporting spatial planning, and reducing coastal risks under future climate change scenarios. Full article

This study aims to assess the role of headwater systems (HS) in enhancing ecological connectivity and supporting Green Infrastructure in the Centre Region of Portugal. Specifically, it identifies restoration opportunity areas within HS by analysing land-use changes over the past 70 years, modelling land-use scenarios to promote ecological resilience, and evaluating connectivity between HS and Natura 2000 sites. The methodology integrates spatial analysis of historical land-use data with connectivity modelling using least-cost path approaches. Results show substantial transformation in HS areas, notably the expansion of eucalyptus plantations and a decline in agricultural land. Approximately 58% of the HS are identified as requiring restoration, including areas within the Natura 2000 network. The connectivity assessment reveals that HS can function as effective ecological corridors, contributing to improved water regulation, soil conservation, gene flow, and wildfire mitigation. A total of 61 potential ecological linkages between Natura 2000 sites were identified. These findings highlight the strategic importance of integrating HS into regional and national Green Infrastructure planning and supporting the implementation of the EU Biodiversity Strategy for 2030. The study recommends prioritising headwater restoration through multi-scale planning approaches and active involvement of local stakeholders to ensure sustainable land-use management. Full article