Search Results (309)

Future lunar south pole missions face dual challenges of highly variable illumination and rugged terrain that directly constrain rover mobility and energy sustainability. To address these issues, this study proposes a dynamic illumination-constrained spatio-temporal A* (DIC3D-A*) path-planning algorithm that jointly optimizes terrain safety and illumination continuity in polar environments. Using high-resolution digital elevation model data from the Lunar Reconnaissance Orbiter Laser Altimeter, a 1300 m × 1300 m terrain model with 5 m/pixel spatial resolution was constructed. Hourly solar visibility for November–December 2026 was computed based on planetary ephemerides to generate a dynamic illumination dataset. The algorithm integrates slope, distance, and illumination into a unified heuristic cost function, performing a time-dependent search in a 3D spatiotemporal state space. Simulation results show that, compared with conventional A* algorithms considering only terrain or distance, the DIC3D-A* algorithm improves CSDV by 106.1% and 115.1%, respectively. Moreover, relative to illumination-based A* algorithms, it reduces the average terrain roughness index by 17.2%, while achieving shorter path length and faster computation than both the Rapidly-exploring Random Tree Star and Deep Q-Network baselines. These results demonstrate that dynamic illumination is the dominant environmental factor affecting lunar polar rover traversal and that DIC3D-A* provides an efficient, energy-aware framework for illumination-adaptive navigation in upcoming missions such as Chang’E-7. Full article

Recognizing the critical role of polar Sea Ice Concentration (SIC) in climate feedback mechanisms, this study presents the first comprehensive investigation of China’s Fengyun-3E(FY-3E) GNOS-II Global Navigation Satellite System Reflectometry (GNSS-R) for bipolar SIC retrieval. Specifically, reflected signals from multiple Global Navigation Satellite Systems (GNSS) are utilized to extract characteristic parameters from Delay Doppler Maps (DDMs). By integrating regional partitioning and dynamic thresholding for sea ice detection, a Random Forest Regression (RFR) model incorporating a rolling-window training strategy is developed to estimate SIC. The retrieved SIC products are generated at the native GNSS-R observation resolution of approximately 1 × 6 km, with each SIC estimate corresponding to an individual GNSS-R observation time. Owing to the limited daily spatial coverage of GNSS-R measurements, the retrieved SIC results are further aggregated into monthly composites for spatial distribution analysis. The model is trained and validated across both polar regions, including targeted ice–water boundary zones. Retrieved SIC estimates are compared with reference data from the OSI SAF Special Sensor Microwave Imager Sounder (SSMIS), demonstrating strong agreement. Based on an extensive dataset, the average correlation coefficient (R) reaches 0.9450 in the Arctic and 0.9602 in the Antarctic for the testing set, with corresponding Root Mean Squared Error (RMSE) of 0.1262 and 0.0818, respectively. Even in the more challenging ice–water transition zones, RMSE values remain within acceptable ranges, reaching 0.1486 in the Arctic and 0.1404 in the Antarctic. This study demonstrates the feasibility and accuracy of GNSS-R-based SIC retrieval, offering a robust and effective approach for cryospheric monitoring at high latitudes in both polar regions. Full article

Climate-driven sea ice decline is accelerating the commercial use of Arctic routes and raising the need for Green Shipping Corridors that couple decarbonization with safety and ecosystem protection. This study introduces the concept of Arctic Green Maritime Data—environmental, meteorological, operational, and emission datasets generated in polar navigation—and examines how the EU Data Act can serve as a legal–institutional backbone. Using a multilayered integrative analysis, we (i) interpret core provisions on user access, portability, compensation, public-interest requests, cloud switching, and interoperability; (ii) map the Act’s roles of data holder, user, and recipient onto shipping stakeholders; (iii) assess whether polar operational datasets qualify as “data generated through the use of a product”; and (iv) derive a contractual architecture for corridor operations. We propose a three-layer governance model: firm-level instruments (a Standard Arctic Green Maritime Data Transaction Agreement, enterprise data governance architecture, and FRAND (Fair, Reasonable, and Non-Discriminatory) based contracting), association-level tools (industry model terms, public-purpose data protocols, and a neutral data-trust intermediary), and IMO-level integration aligning EU Data Act principles with Polar Code and MARPOL. The analysis showed that structured rights and obligations reduce vendor lock-in, enable safe public-interest data flows (with emergency access and fair compensation), and improve interoperability across clouds and jurisdictions. The results provide implementable pathways for shipping companies to turn Arctic Green Maritime Data into strategic assets while supporting sustainable and resilient green shipping corridor operations. Full article

Electrokinetics has established itself as a central pillar in microfluidic research, offering a powerful, non-mechanical means to manipulate fluids and analytes. Mechanisms such as electroosmotic flow (EOF), electrophoresis (EP), and dielectrophoresis (DEP) re-main central to the field, once more layers of complexity emerge heterogeneous interfaces, viscoelastic liquids, or anisotropic droplets are introduced. Five research directions have become prominent. Field-driven manipulation of droplets and emulsions—most strikingly Janus droplets—demonstrates how asymmetric interfacial structures generate unconventional transport modes. Electrokinetic injection techniques follow as a second focus, because sharply defined sample plugs are essential for high-resolution separations and for maintaining analytical accuracy. Control of EOF is then framed as an integrated design challenge that involves tuning surface chemistry, engineering zeta potential, implementing nanoscale patterning, and navigating non-Newtonian flow behavior. Next, electrokinetic instabilities and electrically driven micromixing are examined through the lens of vortex-mediated perturbations that break diffusion limits in low-Reynolds-number flows. Finally, electrokinetic enrichment strategies—ranging from ion concentration polarization focusing to stacking-based preconcentration—demonstrate how trace analytes can be selectively accumulated to achieve detection sensitivity. Ultimately, electrokinetics is converging towards sophisticated integrated platforms and hybrid powering schemes, promising to expand microfluidic capabilities into previously inaccessible domains for analytical chemistry and diagnostics. Full article

The civil Global Navigation Satellite System (GNSS) signal is broadcast with an open structure, making it vulnerable to spoofing attacks. Incorporating authentication data into GNSS signals is a significant measure to enhance system security. Precise Point Positioning (PPP) technology has garnered extensive attention for its ability to provide real-time services with centimeter-level accuracy. The PPP service features a high data update rate, with the validity period of the data being approximately ten to twenty seconds. This imposes more stringent requirements on the authentication data rate and the authentication time. Code Shift Keying (CSK) technology has emerged as a key candidate for satellite-based PPP signal design, as it can increase the data rate without requiring additional spectrum resources. This paper investigates authentication methods for CSK-modulated satellite-based PPP signals. Two approaches are proposed: phase modulation authentication and polarity modulation authentication. Simulation and analysis results indicate that the PPP signal with phase modulation authentication experiences less carrier-to-noise ratio (C/N₀) loss and has a higher detection probability. In contrast, the signal with polarity modulation authentication does not suffer from C/N₀ loss and achieves a higher data rate and a shorter authentication time. These findings can serve as valuable references for future GNSS signal design. Full article

High-resolution and high-precision marine gravity reference maps are core prerequisites for the practical application of gravity-assisted inertial navigation algorithms, and their accuracy directly determines the performance of the navigation system. In view of the problems existing in the current geographic rectangular grid gravity reference map, such as severe polar deformation, poor adjacent consistency, and low positioning accuracy in high latitudes, this study introduces a hexagonal grid system to construct a gravity reference map. It systematically analyzes its compatibility and accuracy in navigation applications. A multi-resolution hexagonal grid scheme with a 7-aperture structure is further proposed to meet the characterization requirements of gravitational fields with different complexities. Experimental verification shows that the accuracy of the gravity-assisted inertial navigation algorithm improved by 0.4%, while that of gravity sequence matching improved by 50%. The proposed hybrid resolution grid can achieve a maximum gravity data compression rate of 68% while ensuring navigation accuracy, especially with regard to the computational efficiency and accuracy requirements of gravity-assisted inertial navigation. Full article

In the Arctic region, the navigation and positioning accuracy of shipborne and autonomous underwater vehicle (AUV) integrated Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS) solutions is severely degraded due to poor satellite geometry, frequent ionospheric disturbances, non-Gaussian measurement noise, and strong multipath effects, as well as long-term INS-based dead-reckoning for AUVs when GNSS is unavailable underwater. In addition, the sparse ground-based augmentation infrastructure and the lack of reliable reference trajectories and dedicated test ranges in polar waters hinder the validation and performance assessment of existing marine navigation systems, further complicating the achievement of accurate and reliable navigation in this region. To improve the positioning accuracy of the GNSS/INS shipborne navigation system, this paper adopts a tightly coupled GNSS/INS navigation approach. To further enhance the accuracy and robustness of tightly coupled GNSS/INS positioning, this paper proposes an improved Adaptive Robust Extended Kalman Filter (IAREKF) algorithm to effectively suppress the effects of gross errors and non-Gaussian noise, thereby significantly enhancing the system’s robustness and positioning accuracy. First, the residuals and Mahalanobis distance are calculated using the Adaptive Robust Extended Kalman Filter (AREKF), and the chi-square test is used to assess the anomalies of the observations. Subsequently, the observation noise covariance matrix is dynamically adjusted to improve the filter’s anti-interference capability in the complex Arctic environment. However, the state estimation accuracy of AREKF is still affected by GNSS signal degradation, leading to a decrease in navigation and positioning accuracy. To further improve the robustness and positioning accuracy of the filter, this paper introduces a sliding window mechanism, which dynamically adjusts the observation noise covariance matrix using historical residual information, thereby effectively improving the system’s stability in harsh environments. Field experiments conducted on an Arctic survey vessel demonstrate that the proposed improved adaptive robust extended Kalman filter significantly enhances the robustness and accuracy of Arctic integrated navigation. In the Arctic voyages at latitudes 80.3° and 85.7°, compared to the Loosely coupled EKF, the proposed method reduced the horizontal root mean square error by 61.78% and 21.7%, respectively. Full article

Iceberg detection in Arctic sea-ice environments is essential for navigation safety and climate monitoring, yet remains challenging due to observational and environmental constraints. The scarcity of labelled data, limited optical coverage caused by cloud and polar night conditions, and the small, irregular signatures of icebergs in synthetic aperture radar (SAR) imagery make automated detection difficult. This study evaluates the environmental feasibility of applying a modern deep learning model for iceberg detection within land-fast sea ice. We adapt a YOLOv8 convolutional neural network within the Dual Polarisation Intensity Ratio Anomaly Detector (iDPolRAD) framework using dual-polarised Sentinel-1 SAR imagery from the Franz Josef Land region, validated against Sentinel-2 optical data. A total of 2344 icebergs were manually labelled to generate the training dataset. Results demonstrate that the network is capable of detecting icebergs embedded in fast ice with promising precision under highly constrained data conditions (precision = 0.81; recall = 0.68; F1 = 0.74; mAP = 0.78). These findings indicate that deep learning can function effectively within the physical and observational limitations of current Arctic monitoring, establishing a foundation for future large-scale applications once broader datasets become available. Full article

As global climate warming enhances the navigability of Arctic routes, their navigation value has become prominent, yet ships operating in ice-covered waters face severe threats from sea ice and icebergs. Existing manual observation and radar monitoring remain limited, highlighting an urgent need for efficient target recognition technology. This study focuses on polar environmental target detection by constructing a polar dataset with 1342 JPG images covering four classes, including sea ice, icebergs, ice channels, and ships, obtained via web collection and video frame extraction. The “Grounding DINO pre-annotation + LabelImg manual fine-tuning” strategy is employed to improve annotation efficiency and accuracy, with data augmentation further enhancing dataset diversity. After comparing YOLOv5n, YOLOv8n, and YOLOv11n, YOLOv8n is selected as the baseline model and improved by introducing the CBAM/SE attention mechanism, SCConv/AKConv convolutions, and BiFPN network. Among these models, the improved YOLOv8n + SCConv achieves the best in polar target detection, with a mean average precision (mAP) of 0.844–1.4% higher than the original model. It effectively reduces missed detections of sea ice and icebergs, thereby enhancing adaptability to complex polar environments. The experimental results demonstrate that the improved model exhibits good robustness in images of varying resolutions, scenes with water surface reflections, and AI-generated images. In addition, a visual GUI with image/video detection functions was developed to support real-time monitoring and result visualization. This research provides essential technical support for safe navigation in ice-covered waters, polar resource exploration, and scientific activities. Full article

Ice load is a crucial factor when designing structures for polar vessels. Due to the unpredictable nature of sea ice mechanics and the complexity of ship structures, obtaining ice load characteristics through full-scale measurements is considered more effective and reliable. However, conducting full-scale tests in the Arctic for China can be time-consuming and expensive. Using the natural ice fields in the Bohai Sea for full-scale tests can provide valuable insights into the study of ice load. To study ice load characteristics, full-scale measurements were carried out during icebreaker navigation trials in the ice zone of Bohai Sea. Distributed shear strain sensors were installed to measure the ice-induced structural strain on the starboard of the bow, and the local ice loads were determined based on the influence coefficient matrix method. Additionally, video cameras were utilized to record ice conditions, including ice type and thickness. By analyzing the data, the Rayleigh separation method was used to extract the process of ice load action. Statistical analysis was performed on the peak ice load values, with a particular emphasis on the various types of sea ice, ice thickness, and ship speed. The results show that the action period, peak value, mean value, and waveform of ice loads obtained in the full-scale measurement are consistent with the full-scale data of other icebreakers. The conclusion supports the effectiveness and feasibility of conducting ship ice load characteristic testing in the Bohai Sea. Full article

Feminist and women religious scholars seek reconciliatory resources beyond the conservative/progressive binary that fuels conflicts, undermines communication and agency, and sustains oppressive structures. Drawing on feminist theology and religious anthropology, this qualitative study investigates how progressive clergywomen in South Korea exercise agency to move beyond this binary. It argues that their agency integrates resistance with measured accommodations of conservative elements, reflecting reconciliatory self-reconfigurations shaped by Korean historical and theological shifts across democratization, an intertwined conservative—progressive landscape, and personal influences, especially family. Central to this shift are (1) anthropological and theological reorientations that emphasize human vulnerability, resilient Christian faith/identity, and a shared foundation of Christian life transcending dichotomies—faith/activism, personal/social salvation, and oppressed minjung/oppressor—and (2) a rediscovery of conservative elements, including biblical centrality and everyday sharing. These reorientations find practical expression in contextual sensitivity, embodied faith, and a gradualist approach. Building on earlier scholarship—especially in Korea—that highlights conservative laywomen’s agency, this study analyzes rare cases of progressive clergywomen pursuing change amid tensions with conservative congregations, identifying feasible and sustainable pastoral resources. Their resistance to binary anthropology and their reconciliation of faith and social engagement contribute to renewing Minjung theology. The study further enriches religious anthropology by illuminating the organic interplay between personal and public motivations. Full article

For polar ships, navigation in ice-covered regions can lead to high risk to structural safety. To study the structural risk induced by ice loads, a risk assessment framework is proposed based on a probabilistic analysis. The fatigue failure probability is derived with the first-order second-moment (FOSM) method. Typical ice load cases are extracted as a joint probability distribution of ice thickness and ship speed, based on shipboard measurements. Equivalent fatigue stresses for each case are calculated using a coupled discrete element method (DEM) and finite element method (FEM), and fatigue failure probabilities are obtained via linear cumulative damage theory. The ultimate strength failure probability is derived from the reliability theory. The probabilistic distribution of load-carrying capacity for the bow structure, determined by the moment estimation method, is used as the structural resistance, while the ice load distribution identified from shipboard monitoring is treated as the external load. Considering both the likelihood and consequence of failure, a risk matrix is constructed to assess structural failure risk. Inspection and maintenance intervals are then proposed according to the assessed risk levels. This approach offers a quantitative basis for structural risk management, supporting safe navigation and efficient maintenance planning for polar ships. Full article

Cooperative navigation is a fundamental enabling technology for unlocking the full potential of Unmanned Underwater Vehicle (UUV) clusters in GNSS-denied environments. However, the severe constraints of the underwater acoustic channel, such as high latency, low bandwidth, and non-Gaussian noise, pose significant challenges to designing robust and efficient state estimation and information fusion algorithms. While numerous surveys have cataloged the available techniques, they have remained largely descriptive, lacking a rigorous, quantitative comparison of their performance trade-offs under realistic conditions. This paper provides a comprehensive and critical review that moves beyond qualitative descriptions to establish a novel quantitative comparison framework. Through a standardized benchmark scenario, we provide the first data-driven, comparative analysis of key frontier algorithms—from recursive filters like the Maximum Correntropy Kalman Filter (MCC-KF) to batch optimization methods like Factor Graph Optimization (FGO)—evaluating them across critical metrics including accuracy, computational complexity, communication load, and robustness. Our results empirically reveal the fundamental performance gaps and trade-offs, offering actionable insights for system design. Furthermore, this paper provides in-depth technical analyses of advanced topics, including distributed fusion architectures, intelligent strategies like Deep Reinforcement Learning (DRL), and the unique challenges of navigating in extreme environments such as the polar regions. Finally, leveraging the insights derived from our quantitative analysis, we propose a structured, data-driven research roadmap to systematically guide future investigations in this critical domain. Full article

This systematic review synthesizes a decade of peer-reviewed research (2015–2025) examining the interplay of filter bubbles, echo chambers, and algorithmic bias in shaping youth engagement within social media. A total of 30 studies were analyzed, using the PRISMA 2020 framework, encompassing computational audits, simulation modeling, surveys, ethnographic accounts, and mixed-methods designs across diverse platforms, including Facebook, YouTube, Twitter/X, Instagram, TikTok, and Weibo. Results reveal three consistent patterns: (i) algorithmic systems structurally amplify ideological homogeneity, reinforcing selective exposure and limiting viewpoint diversity; (ii) youth demonstrate partial awareness and adaptive strategies to navigate algorithmic feeds, though their agency is constrained by opaque recommender systems and uneven digital literacy; and (iii) echo chambers not only foster ideological polarization but also serve as spaces for identity reinforcement and cultural belonging. Despite these insights, the evidence base suffers from geographic bias toward Western contexts, limited longitudinal research, methodological fragmentation, and conceptual ambiguity in key definitions. This review highlights the need for integrative, cross-cultural, and youth-centered approaches that bridge empirical evidence with lived experiences. Full article

Global navigation satellite system (GNSS) differential code bias (DCB) and topside ionosphere vertical electron content (VEC) can be estimated using onboard data from low-earth-orbit (LEO) satellites. These satellites provide the potential to make up for the lack of ground-based stations in the oceanic and polar regions and establish a high-precision global ionosphere model. In order to study the influences of different LEO-topside VEC processing methods on estimates, we creatively analyzed and compared the results and accuracy of the DCBs and LEO-topside VEC estimates using two topside VEC solutions—the SH-topside VEC (spherical harmonic-topside vertical electron content) and EP-topside VEC (epoch parameter-topside vertical electron content) methods. Some conclusions are drawn as follows. (1) Using GRACE-A data (400 km in 2016), the monthly stabilities (STDs) of GPS satellite DCBs and LEO receiver DCBs using the EP-topside VEC method are better than those using the SH-topside VEC method. For JASON-2 data (1350 km), the STD results of GPS DCBs using the SH-topside VEC method are slightly superior to those using the EP-topside VEC method, and LEO DCBs using the two methods have similar STD results. However, the root mean square (RMS) results for GPS DCBs using the SH-topside VEC model relative to the Center for Orbit Determination in Europe (CODE) products are slightly superior to those using the EP-topside VEC method. (2) The peak ranges of the actual GRACE-A-topside VEC results using the SH-topside VEC and EP-topside VEC methods are within 42 and 35 TECU, respectively, while the peak ranges of the JASON-2-topside VEC results are both within 6 TECU. Additionally, only the SH-topside VEC model results are displayed due to the EP-topside VEC method not modeling VEC. Due to the difference in orbital altitude, the results and distributions of the GRACE-topside VECs differ from those of the JASON-topside VECs, with the former being more consistent with the ground-based results, indicating that there may be different height structures in the LEO-topside VECs. In addition, we applied the IRI-GIM (International Reference Ionosphere model–Global Ionosphere Map) method to compare the LEO-based topside VEC results, which indicate that the accuracy of GRACE-A-topside VEC using the EP-topside VEC method is better than that using the SH-topside VEC method, whereas for JASON-2, the two methods have similar accuracy. Meanwhile, we note that the temporal and spatial resolutions of the SH-topside VEC method are higher than those of the EP-topside VEC method, and the former has a wide range of usability and predictive characteristics. The latter seems to correspond to the single-epoch VEC mean of the former to some extent. Full article