Search Results (555)

Recent advancements in computer vision, particularly in detection, segmentation, and classification, have significantly impacted various domains. However, these advancements are still strongly tied to RGB-based systems, which are insufficient for applications in industries such as waste sorting, pharmaceuticals, and defence, where material characterization beyond shape or visible colour is necessary. Hyperspectral (HS) imaging captures spatial and spectral information for each pixel and therefore offers a promising route for material-level classification. This study evaluates the potential of combining HS imaging with deep learning for plastic material classification. The work includes: (i) the design of an experimental setup with a HS line-scan camera, conveyor, and controlled illumination; (ii) the construction of an object-disjoint dataset of HDPE, PET, PP, and PS samples with semi-automated mask generation and Raman spectroscopy-based labelling; and (iii) the development of P1CH, a lightweight pixel-wise 1D convolutional hyperspectral classifier. On object-disjoint test images, P1CH achieved 97.44% all-pixel accuracy. A boundary sensitivity analysis, reported separately because semi-automated labels are uncertain at material/background interfaces, yielded 99.94% accuracy after excluding a pre-defined two-pixel border band. Additional ablation, baseline, and robustness analyses show that the proposed pixel-wise spectral approach is effective for small fragments, visually similar plastics, and overlapping materials, while black or very dark plastics remain challenging under the present camera and illumination configuration. Full article

To address the risks of cross-border transmission of pathogenic microorganisms posed by the failure or non-compliance of shipboard ballast water treatment systems, ports urgently require efficient and flexible emergency response solutions. This study presents a novel, containerized, integrated ship-to-shore emergency response system specifically designed for the rapid inactivation of pathogenic microorganisms in ballast water. The core innovation lies in the integration of a three-degree-of-freedom (3-DOF) hydraulic robotic arm, a vision and positioning system, and a dynamic inflatable sealing structure designed for rapid, automated docking with a ship’s ballast water discharge outlet (DN250), thereby enhancing operational safety and efficiency. The system employs a purely physical treatment process of “ultrasound (US) pre-treatment + dual-stage ultraviolet (UV) disinfection,” allowing for reception and treatment without secondary chemical pollution. The integrated treatment train, consisting of US (30 kHz, 7.6–12 kW, minimum acoustic energy density ≥ 0.45 J/cm²) followed by dual-stage UV disinfection (minimum UV dose: 147 mJ/cm²), maintained effective microbial inactivation at turbidity levels of 15, 125, 250, and 500 NTU. US alone showed little direct bactericidal effect, whereas the first UV stage achieved log reduction values (LRVs) of 3.31–4.13, and the complete US + UV + UV process achieved total LRVs of 5.07–7.34 for Escherichia coli. The results showed that dual-stage UV disinfection was key to achieving high inactivation efficacy (p < 0.001), while ultrasound, despite its limited direct bactericidal effect, may have facilitated downstream UV disinfection within the sequential treatment train. This system not only fills a critical gap in port biosecurity emergency infrastructure but also provides an experimentally validated, efficient, environmentally friendly, and flexibly deployable shore-based solution. Full article

Introduction: Despite more than two decades of implementation, the European Water Framework Directive (WFD) still faces major challenges in achieving good ecological status across European water bodies. Key limitations persist in connectivity restoration, transboundary harmonization, monitoring network design, and biological assessment of complex systems such as large rivers, reducing the Directive’s capacity to provide consistent ecological diagnoses and support effective river basin management. Objective: This work had four objectives: (I) incorporate ecological status into connectivity assessments; (II) evaluate harmonization in Iberian transboundary basins; (III) optimize the national fish monitoring network through co-creation; (IV) develop a fish-based multimetric index for Portuguese large rivers. Methodology: The work combined four approaches: (1) graph-based connectivity analysis integrating the probability of achieving good ecological status to evaluate functional connectivity across European river networks; (2) cross-border comparison of ecological classifications between Portugal and Spain in shared Iberian basins; (3) optimization of the Portuguese fish monitoring network through a co-creation approach involving the national authority; (4) development of a fish-based multimetric index designed for Portuguese large rivers. Results: Integrating ecological status into connectivity analyses reduced estimated connectivity and highlighted the combined effects of fragmentation and degradation. Cross-border comparisons showed that formal harmonization does not ensure consistent ecological classification. The optimized monitoring networks improved ecological representativeness without increasing sampling effort, while co-creation ensured operational feasibility. The new fish index for large rivers captures spatial variation in ecological quality and responds to pressure gradients, addressing a recognized methodological gap. Conclusions: Improving WFD implementation requires progress across multiple complementary components rather than isolated advances. More effective river management depends on integrating ecological processes, comparable assessment outputs, representative monitoring networks, and system-specific tools. These approaches provide transferable pathways for strengthening freshwater assessment and supporting more coherent river restoration and management across Europe. Full article

This study aimed to systematically categorize and critically analyze the feasibility of developing a cultural resource-based tourism route in Betong District, Yala Province, the southernmost area of Thailand, which is called “the city in the mist.” Research and development techniques were employed using a simulated map from an information system and community forums to create and revise a cultural resource-based tourism map in these areas: the Aiyoeweng, Tano Maero, Betong, and Than Nam Thip Subdistricts. The participants from five communities, 10 people per community, totaling 50 participants, were selected through purposive sampling to join in drafting a cultural resource map by pinpointing important areas in each subdistrict. The fieldwork data collected in each subdistrict were categorized and the content was analyzed to examine the feasibility of the approach to creating a map based on cultural resources. The results found that the tourism patterns resulting from a strong resource base could be divided into tangible and intangible cultural resources. The selected resources include local food, learning centers, tourist attractions, interesting entertainment activities, and community service centers. These were then used to create a simulated map, which was analyzed to determine the feasibility of a tourism route based on resource capital, abundant forests, cultural capital in historical sites, and social capital that were covered in community tourism policies, plans, and guidelines for tourism management to achieve maximum benefits, resulting from the community process that had to jointly design the process. The results of this study are part of the restoration of tourism based on resources for income management and for local organizations to expand and upgrade tourism to the regional economic zones in the southern border provinces. Full article

This article examines the process of the European Union’s geopolitisation within the context of intensifying geopolitical competition and uncertainty in a shifting global order. It focuses on how this process reshapes the EU’s character as a political actor and identifies the structural constraints that limit its geopolitical agency. The study employs a conceptually oriented qualitative research design based on interpretative analysis and the triangulation of theoretical frameworks, policy documents, and selected empirical cases. The findings demonstrate that the EU’s geopolitical turn does not represent a transformation into a traditional state-centric power; rather, it constitutes a process of strategic adaptation within a complex multi-level governance system. Furthermore, geopolitisation manifests unevenly across policy domains, with the most pronounced impacts identified in enlargement, geoeconomics, and external border management. Despite rising ambitions, the EU’s capacity to act remains constrained by internal fragmentation, dependence on member states, and challenges regarding political legitimacy. The primary contribution of this article lies in its conceptualisation of EU geopolitisation as a hybrid and multidimensional process—one that is not a linear transformation towards a traditional geopolitical power, but an outcome of the interaction between regulatory, market, and strategic logics. These findings contribute to the ongoing academic debate by highlighting the necessity of theoretical pluralism when examining the EU in a geopolitical context. Full article

Amid rising geopolitical fragmentation and growing uncertainty in global financial systems, Central Bank Digital Currencies (CBDCs) are increasingly viewed as a potential innovation in cross-border digital payments. This paper provides a systematic review of the literature on CBDCs, with a particular focus on their role in cross-border payment systems, while also considering broader implications for monetary power and geopolitical realignment. Using a PRISMA-based review approach, complemented by bibliometric mapping, the study synthesizes existing research across economic, technological, institutional, and geopolitical dimensions. Unlike prior studies that primarily examine technical design features or domestic monetary implications, this review develops an integrated framework that situates CBDCs within the evolving architecture of cross-border digital payment systems in a fragmented global environment. The evidence suggests that CBDCs can enhance cross-border payment efficiency by reducing transaction costs, shortening settlement times, and enabling more direct transfer mechanisms that bypass traditional correspondent banking networks. At the same time, the literature highlights several critical challenges, including interoperability constraints, regulatory divergence, privacy concerns, and cybersecurity risks. Importantly, the findings also point to the potential emergence of parallel digital currency ecosystems, which may reinforce existing financial fragmentation rather than fully resolve it. Overall, CBDCs should be understood not only as technological innovations in digital payments but also as strategic instruments with implications for monetary sovereignty and global economic influence. Their long-term impact on cross-border payment systems will depend on the development of interoperable standards, coordinated regulatory frameworks, and sustained international cooperation. By bringing together fragmented strands of research, this study contributes to a more comprehensive understanding of how CBDCs are reshaping both digital payment infrastructures and the broader global financial order. Full article

Income inequality remains a central impediment to inclusive growth, yet whether government-led digital infrastructure programs mitigate or exacerbate distributional disparities is empirically contested. Exploiting the staggered rollout of China’s “Broadband China” (BBC) demonstration cities as a quasi-natural experiment, this study employs a multi-period difference-in-differences (DID) framework on a panel of 281 prefecture-level cities spanning 2009–2022 to estimate the designation effects of national digital infrastructure policy under the DID identifying assumptions. After parallel-trends validation, permutation-based placebo tests, and propensity score matching, the baseline estimates indicate a dual distributional pattern: BBC designation is associated with a wider urban-rural income gap and lower within-prefecture nighttime-light-based spatial income inequality. Candidate-channel analysis provides evidence consistent with financial deepening and factor mobility as plausible pathways: expanded financial coverage and cross-regional labor reallocation are associated with spatial convergence, whereas asymmetric usage depth and selective labor mobility reinforce urban-rural divergence. Exploratory heterogeneity analysis across four institutional dimensions, officials’ political promotion incentives, local fiscal capacity, traditional infrastructure endowments, and urban hierarchy, further shows that this distributional pattern varies across local contexts. Furthermore, this study extends the analytical lens to the spatial dimension by employing a spatial DID framework. The results identify significant cross-border externalities characterized by cross-prefecture spillovers associated with lower within-prefecture nighttime-light-based spatial income inequality in neighboring cities. These findings provide an integrated policy-evaluation framework that disentangles the complex, multidimensional distributional consequences of digital infrastructure investment, offering actionable insights for designing more equitable digital public policies in developing economies. Full article

Background/Objectives: COVID-19 vaccine resistance was detrimental to herd immunity and worsened COVID-19 morbidity and mortality during outbreaks. Despite more evidence showing reactionary behavior among residents exposed to vaccine mandates, little research has been conducted on the effects of state proof-of-vaccine (POV) mandate bans in the United States (US). We sought to investigate the causal effects of POV mandate bans, overall and stratified by policy passage via executive order or state legislature, on first-dose COVID-19 vaccinations. Methods: In the contiguous US, 21 states enacted POV mandate bans from 8 February 2021–25 October 2021. Using a geographic regression discontinuity design, we selected treatment and control counties within 150 miles of the POV mandate ban state border. The resulting sample was 4612 county-observations and 2466 unique counties. We conducted two-way fixed-effects estimation to compare changes in weekly, first-dose COVID-19 vaccinations among individuals <65 years old before and after POV mandate ban enactment between treatment and control counties. Results: Among executive order POV mandate ban counties, we saw an additional increase in weekly, first-dose COVID-19 vaccinations following POV mandate ban enactment when compared to controls. There was an additional 38.2% increase in Weeks 1–2, 40.6% in Weeks 3–4, 41.3% in Weeks 5–6, and 43.9% in Weeks 7–8. Conclusions: While seemingly counterintuitive, these findings follow Psychological Reactance Theory. Once the perceived threat to freedom was removed, reactance to COVID-19 vaccinations declined and constituents received the COVID-19 vaccine of their own volition. Future public health efforts should consider potential reactance to mandatory policies and tailor efforts to community values. Full article

Open fiscal data in Ecuador remains largely unexplored beyond basic descriptive reporting, despite its potential for territorial intelligence and fiscal planning. This study examines how taxpayers are distributed across Ecuador’s provinces and economic sectors by applying a Big Data pipeline built on Apache Spark 3.5, PostgreSQL 14/PostGIS 3.2, and Python 3.11 spatial libraries to the SRI Tax Registry, comprising approximately 2.5 million records. The analysis combined K-Means and DBSCAN clustering with spatial autocorrelation methods, including Moran’s Index and LISA, to identify concentration patterns and territorial dependencies. The findings show that 68% of taxpayers are located in three provinces, namely Pichincha (34%), Guayas (24%), and Azuay (10%), with a spatial Gini coefficient of 0.61 reflecting considerable fiscal inequality across the country. A Global Moran’s Index of 0.49 (p < 0.001) confirms that neighboring provinces tend to share similar taxpayer densities, while LISA revealed five High–High clusters in major urban centers and six Low–Low clusters in the Amazon region and northern border. DBSCAN identified 27 spatial groupings, including secondary economic nuclei in cities like Ambato, Riobamba, and Machala that autocorrelation models alone do not capture. The methodology is replicable and offers a practical basis for designing place-based fiscal policies in similar contexts. These results provide tax authorities and regional planners with an empirically grounded, scalable framework for identifying territories with fiscal formalization gaps and designing geographically targeted interventions to reduce territorial inequality in Ecuador and in comparable developing-country contexts. Full article

Due to multiple anthropogenic drivers, coastal wetlands have lost roughly 50% of their historical coverage, and deterioration is accelerating with rising sea levels. Thin-layer placement (TLP), the spreading of sediment dredged from nearby water bodies across existing wetlands or shallow mudflats to raise surface elevation, has emerged as a viable approach to sustain and restore these habitats. Strategies for the prioritization of site selection and design elements for TLP interventions remain unclear; a gap that must be closed to coordinate dredging with wetland restoration efficiently, given time, financial, and sediment constraints. Here, we present a transferable workflow to plan TLP projects, including systematic assessment of restoration needs, development of sediment application options, and prioritization of project sites that leverage publicly available remote-sensing data products and stakeholder input. We demonstrate its applicability in a rapidly deteriorating salt marsh–mangrove co-dominated system on the Atlantic coast of Florida. Guided by stakeholder priorities for storm-surge mitigation and habitat improvement, we tracked long-term (1952–2023) changes in vegetated wetland coverage to quantify loss trends and establish historic habitat borders as restoration targets. We then summarized short-term (2010–2023) habitat-mosaic shifts to resolve plant-species composition changes. In our focal system, long-term analyses revealed hotspots (zones 1 and 7) of >35% vegetation loss, while short-term analyses showed a 180% mangrove expansion and cordgrass degradation across all zones, suggesting a nuanced, tailored approach to sediment application. Taken together, this workflow provides a data-driven, stakeholder-informed process for TLP site prioritization to restore threatened wetlands, bolster coastal resilience, and maximize stakeholder benefits in our demonstration system in northeast Florida and, more broadly, to other dynamic coastlines. Full article

Cross-border e-commerce offers consumers broader product access, yet uncertainty surrounding returns continues to suppress online purchase decisions. This study conceptualizes digital local return services as a digital assurance mechanism in cross-border e-commerce rather than merely a reverse logistics function. Drawing on UTAUT2, perceived risk theory, and trust theory, we develop and test a research model using survey data from South Korean consumers with prior experience of digital local return services (LRS). Structural equation modeling (SEM) is used to test the proposed relationships, and artificial neural networks (ANN) are employed to capture nonlinear effects and compare the relative importance of key predictors. Qualitative interview evidence is further incorporated to enrich the interpretation of the findings. The results show that performance expectancy, effort expectancy, facilitating conditions, and hedonic motivation significantly reduce perceived risk. Perceived risk, in turn, exerts a strong negative effect on purchase intention and weakens consumer trust. Additional ANN results indicate that hedonic motivation and facilitating conditions are particularly influential in lowering perceived risk, while perceived risk is more important than trust in predicting purchase intention. These findings show that digital return service design shapes consumer decisions primarily through risk reduction rather than trust enhancement alone. The study contributes to digital commerce research by explaining how return service design functions as a customer-facing platform assurance mechanism that improves conversion in cross-border online retailing. Full article

Using the recently created contemporaneous and lagged R²-decomposed connectedness paradigm, this study examines the dynamics of return transmission between large South African banks and two top international banks, J.P. Morgan and BNP Paribas. The analysis makes a distinction between delayed (liquidity-driven) propagation mechanisms and instantaneous (information-driven) spillovers, using daily stock returns from 2015 to 2024. With a Total Connectedness Index of 44.14%, which is driven mostly by contemporaneous transmission, the results demonstrate a high degree of systemic interdependence and rapid assimilation of global information across banking stocks. We find smaller lagged spillovers which become much more intense during stressful events like COVID-19 in 2020, the conflict between Russia and Ukraine in 2022, and the banking instability involving the United States and Switzerland in 2023. These findings are conditioned by funding pressures, liquidity limits, and slow portfolio rebalancing. In the South African financial system, Standard Bank and Nedbank consistently act as net transmitters of shocks, whereas J.P. Morgan and BNP Paribas primarily act as net receivers, indicating asymmetric cross-border contagion pathways. However, their spillover transmission roles switch during crises. Overall, the results offer fresh empirical insight on how global shocks are absorbed and retransmitted by emerging-market banking systems, providing policy-relevant information for cross-border supervisory coordination, macroprudential design, and systemic risk monitoring. Full article

This paper proposes a Pulse Train Control (PTC) strategy for the Series Capacitor Buck (SCB) converter operating in Discontinuous Conduction Mode (DCM). Instead of synthesizing a continuous duty ratio, the controller selects between two preset duty ratios in each switching period, and the same binary decision is applied to the two interleaved phases with a ${180}^{\circ }$ phase shift. A reduced one-dimensional control-oriented discrete-time map is derived from output charge balance to describe the control cycle-scale regulation dynamics. Based on this map, the bounded-regulation condition is established and the design roles of the pulse pair $(D_H,D_L)$ are clarified. The regulated steady state is shown to be a bounded threshold-crossing periodic motion rather than a static equilibrium, and the evolution of pulse patterns with operating condition is interpreted through border collision transitions. Full switching model and experimental results from a 12-V-to-1-V prototype support the predicted high-pulse fraction trend, the multiplier-based local attraction assessment of annotated periodic pulse patterns, the input voltage-dependent ripple estimate, and the fast large-signal response under representative load step conditions. Full article

To quantify the carbon footprint of cross-border bridges built by Chinese companies in Africa, based on the Janwani Bridge in Tanzania and the life cycle theory, it is divided into five stages: production, transportation, on-site construction, operational maintenance, and demolition and disposal. Using the emission factor method to construct carbon emission models for each stage, while considering cross-border supply chains and the addition of vegetation carbon sinks, we quantify the emissions for each stage. The research is based on the project design stage bill of quantities and construction organization data for prediction and estimation. The energy consumption parameters of construction machinery refer to the Chinese quota standards, and the energy consumption of lighting during the operation period is estimated according to the design parameters. The results show that the total carbon emissions of the life cycle of the bridge is about 41,668,548.20 kgCO₂e, with the production stage being the dominant position (87.48%), and cement and reinforcing steel contributing more than 95% of the emissions during this stage. The operational maintenance stage comes second (7.28%), mainly driven by lighting electricity (accounting for 73.65% of the total emissions in this stage), attributed to the local power grid dominated by fossil fuels. Sensitivity analysis shows that the key factors are ranked as cement > reinforcing steel > electricity > diesel. Considering the reality of insufficient supply of low-carbon materials and weak infrastructure in Africa, emission reduction measures are proposed from three aspects: optimizing concrete mix proportion, controlling construction machinery, and implementing intelligent lighting. The research contribution lies in incorporating the entire cross-border transportation chain and newly added vegetation carbon sinks into the LCA boundary of bridges, while considering the dual attributes of “technology output + localized operation”, and constructing a carbon emission accounting model adapted to the built-up areas of African cities. On this basis, the carbon emission characteristics of the life cycle were quantitatively analyzed, feasible emission reduction measures in the region were proposed, and the carbon reduction potential was calculated, providing scientific basis for low-carbon control of Chinese enterprises’ overseas bridges. Full article

Faced with the challenges of cross-cultural communication of public opinion in emergency events, traditional sentiment recognition methods struggle to accurately capture the complex semantics under multi-lingual and multi-symbol systems. This paper takes the powerful 7.7-magnitude earthquake that struck Myanmar in 2025 as a case study. It constructs a multi-dimensional public opinion annotation framework that integrates four types of semantic information—time, space, subject, and sentiment—by extracting data from multi-source textual materials, including social media, news reports, and government announcements. Building on this foundation, we design an improved Model-Agnostic Meta-Learning (MAML) model that incorporates cultural features to enhance sentiment recognition performance in low-resource cross-linguistic scenarios. Experimental results show that the model outperforms traditional methods in terms of sentiment classification accuracy, cultural semantic deviation rate and metaphor recognition ability. Furthermore, the research reveals the coupling mechanism of public opinion communication of “cultural modulation–agenda game”, and clarifies the influence paths and weight distributions among multiple subjects. The research results provide theoretical support and practical paths for improving the governance capacity of cross-border public opinion in emergency events and the construction of multilingual monitoring models. Full article