Search Results (152)

This article examines how the Ecuadorian national digital press has represented the relationship between criminal violence, declining mobility, tourism contraction, and the erosion of intangible cultural access in Machala, Puerto Bolívar, and the route to Jambelí during 2025. This study aims to explain how mediated representations of insecurity can contribute to the symbolic narrowing of culturally meaningful urban–coastal spaces, even when those spaces remain materially present and formally open. The article responds to a gap in the literature at the intersection of critical heritage studies, media framing, urban fear, and Latin American security studies. The existing research has examined heritage as social practice, media representation of crime, and urban securitization, but has rarely connected these fields to explain how criminal violence erodes lived access to intangible cultural environments in secondary port cities of the Global South. Methodologically, this study applies qualitative content analysis to a purposive corpus of eight focal journalistic texts published in Ecuadorian digital outlets, such as El Universo, El Comercio, Expreso, El Mercurio, Extra, Primicias, GK, and La Hora. Deductive–inductive coding was complemented by descriptive article-level indicators of themes, keyword clusters, and temporal distribution. The findings show that the press did not merely report violent events; it progressively reorganized the symbolic meaning of Machala by re-signifying Puerto Bolívar, the marine environment, the cabotage pier, and the maritime route to Jambelí as spaces of risk, interruption, and conditional access. This study contributes conceptually by defining intangible cultural access and symbolic enclosure, empirically by documenting the mediated erosion of coastal public–cultural life, and practically by proposing integrated policy actions for security governance, cultural reactivation, local commerce, maritime mobility, and responsible public communication. Full article

Coastal waters of eastern Guangdong are important fishing grounds and ecologically sensitive areas in the northern South China Sea, where nekton communities are increasingly affected by environmental heterogeneity and human activities. However, systematic studies on the spatial differentiation and driving mechanisms of nekton communities in this region remain insufficient. This study aimed to clarify the community structure, diversity distribution characteristics, and key driving environmental factors of nekton in the coastal waters of eastern Guangdong, and thereby provide scientific support for an ecological health assessment and sustainable utilization of fishery resources in this region. Based on bottom-trawl survey data from 19 stations in the coastal waters of eastern Guangdong, northern South China Sea, this study systematically analyzed the species composition, dominant species, and diversity distribution pattern of nekton and their correlations with environmental factors using methods including the Index of Relative Importance, Alpha diversity indices, Beta diversity indices, and redundancy analysis. A total of 119 nekton species belonging to three phyla, four classes, 14 orders, and 56 families were collected. Among them, there were 79 fish species (accounting for 66.39%), 36 crustacean species (30.25%), and four cephalopod species (3.36%). The dominant species were Trachypenaeus curvirostris and Portunus sanguinolentus (IRI ≥ 1000). Wilcoxon’s test showed that there were significant differences in the Shannon–Wiener index, Gini–Simpson index, and Pielou’s evenness between the nearshore and offshore groups, while no significant regional difference was observed in the richness index. Cluster analysis, based on the Bray–Curtis distance, divided the 19 stations into five clusters, with significant differentiation in species composition and functional structure within the nearshore group. RDA results indicated that environmental factors collectively explained 99.66% of the variation in community structure. Particulate Inorganic Carbon (PIC), Phosphate (PO₄³⁻), Distance to Port, Summer Maximum Chlorophyll-a (Chl-a), and Total Suspended Matter (TSM) were identified as the key driving factors. The coastal waters of eastern Guangdong boast rich nekton species, with significant differences in community structure between nearshore and offshore areas. The heterogeneity of the natural environment and human activity disturbances jointly shape the nekton diversity pattern in this region. The research results can provide a theoretical basis for regional marine ecological protection and fishery resource management. Full article

Port competition is increasingly shaped by network structures and differentiated functional roles rather than isolated capacity-based comparisons. This study investigates the structural evolution and functional differentiation of the global container port network from a systems perspective by integrating port-cluster identification with role-based functional evaluation. A CONCOR-based approach is employed to delineate structurally cohesive port clusters, while the rank-sum ratio (RSR) method is used to assess ports’ dominant functional roles, including High-Efficiency core, Bridge-Control, and free-form bridging functions. Based on a comparative analysis of network data for 2014 and 2024, the results reveal a transition from a relatively dispersed and multi-polar configuration toward a more concentrated and hierarchical system. Three recurrent spatial structures are identified, reflecting differentiated patterns of trunk connectivity, corridor organisation, and adaptive network flexibility. Functionally, core hubs have expanded their coverage of mainline services, Bridge-Control ports have become increasingly concentrated at strategic chokepoints and transition zones, and free-form bridging ports have enhanced routing flexibility by linking structurally non-overlapping subnetworks. These findings advance understanding of the evolving structure and interdependence of global port competition and provide insights for system-level coordination, cluster-based governance, and coordinated infrastructure planning. Full article

Existing ship trajectory clustering methods often overlook the impact of navigation behaviors (e.g., heading and speed variations) on clustering performance. To address this limitation, a novel ship trajectory clustering method that explicitly incorporates navigation behavior sequence is proposed. Firstly, ship trajectories are preprocessed, and key motion parameters, including the ship Rate Of Turn (ROT) and acceleration at each trajectory point, are calculated through a sliding window. Secondly, by integrating various motion parameters, the navigation behaviors corresponding to trajectory points are classified, and the classification results are taken as the core element to measure the behavior distance between different trajectories. Then, the spatial distance between trajectories is measured based on the Hausdorff distance. Finally, an adaptive Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm is adopted, which fuses behavior distance and spatial distance, to realize ship trajectory clustering that takes navigation behavior into account. Experimental results on Dalian Port and Yantai Port datasets show that: (1) Compared with the classical DBSCAN and Multi-dimensional Density-Based Trajectory Clustering of Applications with Noise (MD-DBTCAN) methods, the proposed method achieves finer granularity of clustering results; (2) Compared with the classical DBSCAN method, the proposed method can effectively distinguish straight-line navigation trajectories from trajectories with frequent turning behaviors; compared with the MD-DBTCAN method, the proposed method can distinguish normal straight-line navigation trajectories from trajectories with frequent acceleration and deceleration behaviors. Full article

Automatic Identification System (AIS) trajectories provide valuable spatiotemporal information for maritime route structure mining, but robust extraction of key route nodes remains difficult because raw data are noisy, turning behaviors are easily masked by local fluctuations, and conventional Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is sensitive to fixed parameters and ignores heading differences. To address these issues, this study proposes a key route node extraction framework based on multi-constraint turning-point identification and heading-aware adaptive DBSCAN (HA-DBSCAN). Raw AIS data are first cleaned, segmented, and compressed using a heading-aware Douglas–Peucker strategy to reduce redundancy while preserving geometric and directional characteristics. Valid turning points are then identified by jointly considering heading change rate, geometric curvature, and temporal stability. Finally, HA-DBSCAN integrates a heading-aware distance metric, adaptive neighborhood estimation, and density-aware MinPts optimization to cluster turning points and extract representative route nodes. Experiments using AIS data from the Ningbo–Zhoushan Port area retained 287,614 valid records and 754 continuous trajectory segments, from which 1710 turning points were identified. The proposed method generated 45 stable clusters with a noise ratio of 0.0450 and route coverage of 95.5%. These results indicate that, within the current study setting, the framework can distinguish crossing routes, adapt to heterogeneous traffic densities, and provide an interpretable intermediate layer for subsequent maritime route-structure modeling. Supplementary validation on the same AIS dataset further showed that, compared with DBSCAN, Ordering Points To Identify the Clustering Structure (OPTICS), and HDBSCAN baselines as well as several pipeline ablations, the full framework achieved a more balanced performance in terms of coverage, noise suppression, and avoidance of cluster over-fragmentation. Full article

Coastal port ecosystems serve as critical interfaces between marine environments and anthropogenic activities, yet zooplankton community dynamics in these transitional zones remain poorly understood. This study investigated seasonal variations in zooplankton assemblages and their environmental drivers in the coastal waters surrounding Lanshan Port, northern Yellow Sea, through quarterly field surveys spanning spring to winter. A total of 33 zooplankton species and 16 planktonic larval categories were identified, with Hydromedusa, Copepoda, and planktonic larvae comprising the three dominant groups. Marked seasonal disparities were observed in species richness (spring: 21 species and 11 larvae categories; winter: 8 species and 3 larvae categories), biomass (autumn: 333.7 mg/m³; winter: 34.0 mg/m³), and abundance (spring: 185.3 ind/m³; winter: 25.7 ind/m³). Notably, Aidanosagitta crassa maintained perennial dominance across all seasons. Principal component analysis of dominant zooplankton taxa across seasons indicated that the first two principal components explained 70.05% and 15.97% of the total variance in zooplankton community structure, respectively, with distinct seasonal clustering of sampling sites along PC1 reflecting pronounced seasonal succession in community composition. Redundancy analysis revealed seasonal-specific correlations between dominant taxa and nutrients: nitrate concentration was negatively correlated with the relative abundance of Sergestidae in both spring and summer, whereas ammonium concentration was negatively correlated with Hydromedusa; by contrast, the abundances of Chaetognatha and Tunicata exhibited a significant positive correlation with nitrate. We also found water temperature only drove communities in autumn, while salinity had little effect. These findings elucidate the mechanisms structuring zooplankton communities in temperate coastal port ecosystems and underscore the necessity of seasonally resolved monitoring frameworks for effective marine environmental management. Full article

The concentration of tourist flows along short urban links caused by cruise stops in medium-sized Mediterranean ports exacerbates traffic and localized environmental externalities. This study evaluates the willingness to pay (WTP) of cruise passengers for an electric tram that would connect the Gaženica Port with Zadar’s historic center, an intervention designed to cut travel time and reduce on-street congestion and emissions. Over the course of two seasons, a two-wave, two-site, in-person survey was conducted at the port and in the city center. The instrument adopts a double-bounded dichotomous choice (DBDC) contingent valuation design with randomized starting bids that were calibrated using a pre-test that benchmarked prevailing transport pricing. Primary WTP estimates are obtained from a binary choice model with socio-demographic and environmental covariates; whereby inference relies on cluster-robust errors. Robustness is assessed through three complementary checks that do not require additional data: (i) a bivariate specification to account for within-respondent correlation between first and follow-up bids; (ii) Turnbull nonparametric bounds for the interval-censored WTP distribution; and (iii) starting-point tests using split-sample estimation and bid-set indicators. A spike adjustment based on “no–no at the lowest bid” responses is explored where appropriate. Beyond its methodological contribution, this research advances the sustainable tourism development discourse by quantifying visitors’ financial support for low-emission urban mobility infrastructure that mitigates environmental stresses while preserving residential life quality. The results integrate cruise tourist management with the more general goals of resilient and sustainable urban destinations by offering a decision-ready value input for port-city mobility planning in historic Mediterranean centers. Full article

Building world-class ports requires not only scale expansion but also sustainable structural capability. However, the concept of port “hardcore strength” remains insufficiently clarified and operationalized in existing sustainability and port evaluation research. In this study, port hardcore strength is understood as an integrated capability framework covering infrastructure efficiency and logistics capability, connectivity and regional integration, maritime services and industrial clustering, strategic leadership and innovation capability, and sustainable governance and green port development. This study proposes a sustainability-oriented evaluation framework for assessing the “hardcore strength” of world-class ports through a multi-dimensional indicator system. Methodologically, the study integrates the EWM and CRITIC, and introduces Bland–Altman analysis to examine whether the EWM and CRITIC weight vectors exhibit an obvious systematic bias prior to game-theoretic integration. Using 18 representative global ports from 2019 to 2023 as a case study, the results show that the overall ranking structure remains broadly stable, with Singapore Port and Shanghai Port consistently ranking first and second, respectively, while some middle-ranked ports exhibit moderate positional changes. The findings suggest that differences in world-class port development are rooted not only in operational scale, but also in the coordination of multiple capability dimensions. The study enriches the understanding of world-class port evaluation from a sustainability-oriented perspective. Full article

The global shipping network, which handles over 80% of international trade volume, is increasingly exposed to disruptions from typhoons and other extreme weather events under climate change. However, conventional network vulnerability assessments often overlook the geographically heterogeneous nature of such natural hazards. Here, we introduce a typhoon-related systemic vulnerability model (GMSN-TV) that integrates three core components: typhoon exposure, port network sensitivity, and national adaptive capacity, to quantify the Typhoon Vulnerability Index (TVI) of 1075 major ports across 2017 and 2021. Our analysis reveals four key findings. First, the global shipping network became structurally sparser between 2017 and 2021, with edges declining by 17.84% and network efficiency decreasing by 4.22%, rendering it more susceptible to climate-related disruptions. Second, simulated TVI-based natural attacks and conventional degree-based deliberate attacks induce fundamentally different risk patterns: removing the top 10% high-TVI ports in 2021 caused a 6.3% decline in network efficiency, whereas removing the top 10% hub ports resulted in a 20.1% decline, a difference of 13.8 percentage points; however, natural attacks proved more effective at isolating peripheral ports, generating an isolated node ratio of 1.16% compared to 0.00% under deliberate attacks. Third, when removing the top 50% high TVI ports, the contribution of typhoon vulnerability to network degradation increased from 13.77% in 2017 to 15.87% in 2021. Fourth, high-vulnerability ports exhibit significant spatial clustering, with the Northwest Pacific region (50.8%) and the North Atlantic region (29.5%) collectively accounting for over 80% of global high-vulnerability ports in 2021. Compared to conventional topology-based assessments, the GMSN-TV analytical framework proposed in this study integrates typhoon hazard data with network topology, providing a novel scientific tool with enhanced identification efficacy and accuracy. It successfully captures local network disintegration effects entirely missed by traditional deliberate attacks, revealing an isolated node ratio of 12.5% after removing 70% of high-TVI ports. This demonstrates the tool’s precision in identifying hidden high-risk peripheral nodes, enabling decision-makers to prioritize climate adaptation investments for critical maritime infrastructure more accurately. Full article

With the continuous expansion of maritime trade scale, ports have put forward increasingly higher requirements for transshipment efficiency. Container twist lock disassembly is a key link in the loading and unloading process, and its automation level has a significant impact on the ship’s berthing time at the port. Aiming at the demand of automated disassembly for high-precision 3D vision, this paper proposes a multi-view point cloud local registration method for twist lock recognition. First, Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) is used to extract the keyhole region with the highest overlap in multi-view point clouds, reducing the interference from non-overlapping structures. Then, a two-stage strategy of “coarse registration + fine registration” is adopted: initial alignment is achieved through Random Sample Consensus (RANSAC), and the Iterative Closest Point (ICP) algorithm is improved by combining adaptive distance threshold and normal consistency constraint to complete fine registration. Experimental results show that the proposed method outperforms the global registration scheme in both accuracy and efficiency: the Root Mean Square Error (RMSE) is reduced to 2.15 mm, the Relative Mean Distance (RMD) is reduced to 1.81 mm, and the registration time is approximately 2.41 s. Compared with global registration, the efficiency is improved by 44.2%, which can meet the real-time requirements of continuous operation at automated terminals for the perception link and the time constraints for subsequent manipulator control. The research results preliminarily verify the application potential of this method in the scenario of automated twist lock disassembly. Full article

This systematic review evaluates recent scientific and technological advances in water quality monitoring and pollution alarms for ports, based on records retrieved from seven databases following the PRISMA protocol. A total of 414 documents were screened, resulting in 141 articles (TRL 3) and 56 patents (TRL 4–5). Bibliometric, patentometric, and thematic analyses were conducted using Bibliometrix and ORBIT^®. Results show sustained growth in both academic and technological outputs, with a patent Compound Annual Growth Rate (CAGR) of 32%, compared with 13% for scientific publications, indicating accelerated translation from research to innovation. The conversion rate from scientific research to patenting increased from 14% (2010–2015) to 47% (2020–2023). Analysis of patent legal status reveals that 52% of patent families remain valid (48% granted; 4% pending), while 33% are lapsed, 13% revoked, and 2% expired, reflecting the dynamic and emerging character of the field. Technological ownership is highly concentrated, with China accounting for nearly all active patents, whereas scientific production is more geographically distributed. Thematic analysis identifies four main scientific clusters: environmental monitoring, chemical pollutants, seashore hazards, and eutrophication. The main technological domains of the patents are analysis of biological materials, control, and environmental technologies. Emerging areas of focus at TRL 3 and TRL 4–5 include microplastics, climate-change impacts, aquaculture risks, real-time sensing, IoT-enabled platforms, machine-learning analytics, autonomous monitoring systems, and bioindicator-based early-warning tools. This review provides a quantitative roadmap to support sustainable port operations, coastal ecosystem protection, and progress toward multiple synergistic United Nations Sustainable Development Goals (SDGs). Full article

Coastal cities are complex spatial systems shaped by intertwined economic, environmental, demographic, and governance pressures. This study develops a multidimensional comparative framework to analyze coastal cities in the Black Sea basin across five dimensions: physical–morphological structure, demographic scale, economic–functional profile, transportation and accessibility, and urban quality–governance. To address cross-country data heterogeneity, an ordinal (0–1–2) indicator system is employed and analyzed through multiple multivariate techniques, including Gower dissimilarity, NMDS, Ward hierarchical clustering, MCA, Spearman rank correlation, network analysis, and rank-transformed PCA. Findings indicate that Black Sea coastal cities do not form a single homogeneous typology but cluster around distinct structural patterns. A major axis of differentiation separates port–industrial production-oriented cities from tourism–service-oriented cities, while a considerable group of multifunctional and transitional cities exhibits moderate values across several dimensions. Results show that city typologies are shaped less by national planning regimes than by structural dynamics such as port scale, economic specialization, accessibility, and spatial pressure. By integrating non-metric and metric approaches, the study proposes a context-sensitive and multi-criteria comparative methodology. The findings highlight the need for multi-scalar and multidimensional planning perspectives to better understand structural differentiation in coastal urban systems within semi-enclosed marine regions such as the Black Sea. Full article

With the increasing use of modern technologies in interior design, numerous recent studies have made the effects of kinetic-based design techniques on users’ perceptions a crucial topic, and sustainable performance has emerged as essential. From this standpoint, this study uses a space syntax approach to investigate how human behavioral performance in workspaces is affected by kinetic interiors. Three kinetic-based design strategies were employed to evaluate changes in spatial configuration characteristics, and the relevant terminology was adapted to account for the use of kinetic technology. The paper adopts a comparative analysis model to follow these changes using four syntactic measures: integration, choice, connectivity, and clustering coefficient. The proposed evaluation approach is applied to a traditional office building in Port Said, Egypt, showcasing various aspects of kinetic technology in workspaces. The study’s findings elucidate the correlations between design strategies and the resulting spatial characteristics, guiding designers in evaluating the features of each system and facilitating comparisons between them. Finally, the study’s main aim is to propose a three-step design process as a guideline for creating an integrated kinetic technology design, involving the evaluation of the proposed alternatives to achieve the desired spatial characteristics. Full article

Background: Liquefied natural gas (LNG) distribution in archipelagic regions involves complex trade-offs between transportation, infrastructure investment, and contractual arrangements. While most optimisation studies focus on seller-managed Delivery Ex-Ship (DES) schemes, limited research addresses buyer-managed Free on Board (FOB) frameworks that extend decision responsibility upstream. Methods: This study develops a two-stage integrated optimisation model for long-term LNG supply chain planning under an FOB contractual scheme with time-dependent deterministic demand. Stage 1 determines hub selection, port clustering, vessel sizing, fleet configuration, and endogenous infrastructure capacities using a genetic algorithm, while Stage 2 optimises cluster-level routing sequences. Robustness is assessed through multiple independent runs and sensitivity analysis. Results: A case study of the Nusa Tenggara region identifies Sumbawa as the optimal hub. The upstream segment consistently selects a 65,000 m³ vessel under terminal service capacity constraints, while downstream clusters are served by 3500 m³ and 10,000 m³ vessels depending on distance and demand aggregation. Infrastructure requirements are derived from peak-demand conditions, and the resulting levelised logistic cost is 4.66 USD/MMBtu. Conclusions: The findings demonstrate that FOB arrangements fundamentally reshape network configuration, fleet segmentation, and infrastructure sizing, providing a robust strategic planning framework for buyer-managed LNG supply chains in archipelagic contexts. Full article

The quality of wind power output data directly impacts the assessment of wind farm operational status and the accuracy of power forecasting models. However, due to factors such as sensor precision, communication interference, and the complex harbor environment, raw data collected from port-area wind turbines often contain noise, outliers, and missing values. Without effective cleaning, the resulting power curves can be distorted, reducing the generalization capability of predictive models. To overcome the limitations of traditional outlier detection methods in terms of adaptability and robustness, this study proposes a two-stage port-area wind power data cleaning approach based on dynamic interquartile range and an improved Sigmoid function fitting. In the first stage, an adaptive binning and density-weighting mechanism dynamically expands the interquartile range to identify and remove local outliers across different wind speed intervals. In the second stage, the cleaned wind speed–power data are subjected to secondary fitting and residual analysis using an improved Sigmoid model to detect hidden anomalies and boundary-type outliers. Using measured data from the #1 WT in the Chuanshan Port area as a case study, the experimental results demonstrate that the proposed method achieves high data retention while outperforming the conventional interquartile range, density-based spatial clustering of applications with noise and isolation forest algorithms in terms of the Pearson correlation coefficient (r = 0.93) and the coefficient of determination (R² = 0.89), with mean squared error and root mean squared error reduced to 446.39 kW and 545.58 kW, respectively. The findings verify the efficiency, stability, and practical feasibility of the method for port-area wind power data cleaning, providing a reliable data foundation for wind power forecasting and operational optimization in port environments. Full article