Search Results (457)

The Composite Cycle Engine (CCE) enhances the conventional Joule/Brayton cycle by replacing the high-pressure compressor with a high-quality piston-based gas generator that enables extremely high compression, combustion, and expansion of the working fluid before entering the classic Joule burner. This piston-based topping cycle unlocks much more efficient fuel utilization. This paper studies a CCE concept featuring a system of free double piston (FDP) units for a potential long-range (LR) application in 2045, benchmarked against an advanced turbofan engine representative of the same time frame. In-house-developed simulation tools for the piston system and the overall power plant, as well as aircraft non-linear trade factor analysis, are used for different levels of conceptual assessment. First, the cooling demand inside the FDP system is determined. An engine cycle parametric study is then performed for the design point top-of-climb (ToC). Off-design performance is further studied, demonstrating a 9.3% improvement in thrust-specific fuel consumption (TSFC) in cruise relative to the baseline engine. After incorporating the engine weight and nacelle geometry effects, the engine reaches a total mission fuel burn reduction of around 14.7% compared to the baseline engine. The concept evaluation shows the fuel burn potential of the CCE in the future LR aviation sector and lays the foundation for further climate impact analysis. Full article

With the growing applications of maritime unmanned systems in environmental monitoring, ocean patrol, and emergency response, achieving efficient multi-platform cooperation in complex and dynamic marine environments remains a critical challenge. Unmanned Aerial Vehicles (UAVs) provide flexible and high-coverage sensing capabilities but are constrained by limited energy capacity, whereas Unmanned Surface Vehicles (USVs) offer long endurance and can serve as mobile platforms and energy supply nodes. Existing studies mostly focus on single-factor optimization, lacking a systematic analysis of the coupled relationships among energy, information (communication and positioning), and task decision making. To address this problem, this paper proposes an Energy–Information–Decision Coupling Optimization Method for Cooperative Maritime Unmanned Systems. A unified coupling model is established to integrate task completion, energy consumption, communication delay, and replenishment scheduling into a multi-objective optimization framework. A bi-level optimization algorithm is designed: the upper layer optimizes USV trajectories and energy supply strategies, while the lower layer optimizes UAV path planning and task allocation. A closed-loop adaptive mechanism is incorporated to achieve optimal cooperation under dynamic tasks and energy constraints. Extensive simulations combined with real-world experimental data are conducted to evaluate the method in terms of mission efficiency, energy balance, communication latency, and system robustness, with ablation studies quantifying the contribution of the coupling module. Results demonstrate that the proposed method significantly outperforms non-coupled or single-factor optimization strategies across multiple performance metrics: it achieves a task completion rate exceeding 93%, reduces total energy consumption by approximately 6% and replenishes waiting latency by over 28% compared with the decoupled baseline method. This effectively enhances the cooperative efficiency and robustness of maritime unmanned systems, and provides theoretical and methodological guidance for large-scale, complex ocean missions. Full article

Search and rescue (SAR) operations in mountainous terrain present significant challenges due to complex environments, time-critical decisions, and the need for effective human–AI collaboration. Existing approaches typically employ either fully autonomous systems that lack adaptability to varying task requirements, or fixed human–AI authority allocations that fail to leverage the distinct strengths of humans and AI across different mission phases. This paper proposes Phase-Aware Hierarchical Reinforcement Learning (PAHRL), a novel framework that dynamically allocates decision-making authority between human operators and AI agents based on identified task phases. First, we formulate the mountain SAR problem as a three-phase task structure: Wide Search (WS), Target Confirmation (TC), and Rescue Coordination (RC), and examine the consistency of this decomposition through unsupervised clustering analysis, supported by bootstrap stability (ARI = 0.983 ± 0.083) and multiple clustering metrics. Second, we design an adaptive authority mechanism with four levels (L1: Human-Led to L4: Full-Auto) that automatically adjusts human involvement based on current phase characteristics and environmental uncertainty estimates. Third, we introduce a priority-based task execution module that ensures efficient resource allocation across multiple rescue objectives while respecting authority constraints. Extensive experiments demonstrate that PAHRL outperforms baseline methods, achieving a 20.9% higher success rate compared to standard PPO (59.0% vs. 48.8%) and 66.7% improvement over heuristic approaches. PAHRL maintains 96.9% precision even under 60% noise conditions with only 0.09 false rescues per episode. Ablation studies further reveal that phase awareness serves as a critical robustness mechanism; removing phase detection causes complete mission failure under noisy conditions. These results evaluate that phase-aware dynamic authority allocation significantly enhances both efficiency and robustness in human–AI collaborative SAR missions. While demonstrated in a proof-of-concept simulation with computational human models, validation with real operators and more complex environments remains essential before operational deployment. Full article

This paper focuses on T. C. Chao’s (Zhao Zichen, 赵紫宸, 1888–1979) poeticizing theology practice, in which he applied poetry to expound and express theological thought. By employing research methodology that integrates historical and logical analysis, this study examines the historical context and the author’s personal theological mission, so as to investigate the formation of his poeticizing theology. This paper analyzes T. C. Chao’s poetry from multiple aspects, including the form, the expression, the core of his thoughts and the poetry’s peculiarities. We found that T. C. Chao’s poeticizing theology shows cultural fusion and a mystic inclination at the textual level, reflecting peculiarities in contextualization, ethics and indigenization at the theological level. These characteristics of T. C. Chao’s poeticizing theolog provide great significance in offering spiritual comfort, advancing indigenous theology, and responding to contemporary intellectual trends. Furthermore, it remains instructive for current practices of cross-cultural fusion that take Chinese culture as the main subject, and emphasize the fusion of inner spirituality and creative transformation. Full article

To advance our understanding of atmospheric processes and climate dynamics, improved knowledge of outgoing long-wave radiation (OLR) spectral emission is essential. The FORUM mission, selected for the ninth cycle of the European Space Agency’s Earth Explorer programme, is specifically designed to address the long-standing observational gap in the far-infrared (FIR) spectral region. When combined with measurements from the IASI-NG instrument, FORUM will provide complete spectral coverage of Earth’s OLR emission (spanning 100 to 2760 cm⁻¹ wavenumber, or 3.62 to 100 μm wavelength), thereby enabling robust climate model validation and enhanced understanding of climate change processes. While IASI-NG’s primary mission is to support numerical weather prediction, FORUM is designed to measure key climate variables, which also enable the retrieval of atmospheric parameters in the troposphere and lower stratosphere. In this study, we assess the information content of FORUM and IASI-NG measurements for atmospheric profiling through a simulation-based approach. Synthetic retrieval products are generated using a linearized formulation of the retrieval transfer function, allowing an efficient and physically consistent evaluation of the sensitivity of the two instruments to atmospheric temperature and water vapor profiles. The analysis reveals a non-negligible sensitivity of FORUM to atmospheric temperature extending into the stratosphere, resulting in significant information content at altitudes higher than previously reported. This finding highlights the potential of far-infrared observations to contribute to atmospheric temperature profiling beyond the lower troposphere. The complementary capabilities of FORUM and IASI-NG suggest that their combined use can enhance the characterization of the atmospheric thermal structure. These results represent a first step toward evaluating the potential role of FORUM Level-2 products in future numerical weather prediction applications. Full article

Background/Objectives: The healthcare sector, despite its mission to protect health, is a major consumer of resources and emitter of greenhouse gases, giving rise to an ethical and governance paradox: how to reconcile the duty of care with the environmental impact of its activities. In the Spanish healthcare system, which is highly decentralized and regulated at multiple levels, this tension shapes the implementation of environmental policies. This study analyzes the governance and implementation of environmental regulations in Spanish healthcare institutions and the associated experiences. Methods: A qualitative, exploratory, descriptive study was conducted using effective meetings and semi-structured interviews with 20 participants, working in healthcare provision and environmental management within health institutions, across different regions of Spain, between September 2024 and November 2025. In addition, a documentary analysis of relevant regulations was undertaken. Results: The results indicate that Spanish healthcare institutions improve their environmental performance through the implementation of standards such as ISO or EMAS, although their adoption varies according to each institution’s level of development in environmental management. In addition, differences were observed in the environmental dynamics of healthcare institutions, linked to the decentralization of the Spanish healthcare system, as well as administrative barriers to accessing funding and gender disparities in environmental leadership. Conclusions: The standardization of environmental regulations and measures across the country, along with strengthening organizational capacity, could strengthen progress toward more sustainable healthcare. Full article

The Atomic Clock Ensemble in Space (ACES) mission, currently operating aboard the International Space Station (ISS), is designed to provide high-precision time and frequency measurements and to test fundamental aspects of relativistic physics. Gravitational redshift (GRS), a fundamental prediction of General Relativity (GR), implies that clocks positioned at different gravitational potentials experience relative time dilation. Previous GRS experiments have focused primarily on microwave technologies, with negligible experimental coverage in the optical domain, particularly for ground-to-space links. Motivated by the European Laser Timing (ELT) experiment and the high-precision laser-cooled cesium clock aboard ACES, we introduce and evaluate an optical time-transfer method designed to achieve high-accuracy measurements of GRS. In the absence of actual ELT/ACES optical data, a high-fidelity numerical simulation framework was developed to assess the performance of this method. The framework incorporates representative ELT/ACES mission parameters, including the space-based cesium clock and the H-MASER clock located at the reference ground station, both providing frequency stability at the level of ${10}^{-15}$ for 1000 s averaging time. Applying a $\pm 1\sigma$ filtering criterion, we obtain a simulated dataset comprising 33 ELT/ACES passes, representing a total observation time of 4.38 h over a single week. Analysis of this high-fidelity dataset reveals a GRS deviation from GR of $(-7.19\pm 0.63)\times {10}^{-5}$, achieving a 3.4 orders of magnitude improvement over the best previous laser-ranging experiment conducted at the University of Maryland (UMD), USA, 51 years ago. These simulation results demonstrate that the optical time-transfer link constitutes a powerful tool for testing fundamental physics and, when combined with next-generation optical atomic clocks, enables unprecedented capabilities in space-based timekeeping and geoscience applications. Full article

Organizations communicate across many channels, yet official websites remain a controlled, authoritative space where firms articulate identity and strategy. This study examines how Croatia’s top enterprises (n = 100) describe themselves on their websites and which emotional tones they use to signal strategic intent. Our goal is to identify recurring strategic signifiers and map distinct sentiment profiles in corporate narratives. We compiled company descriptions from official sites; texts were originally in Croatian and machine-translated into English, and all analysis was conducted on the English corpus. Using lexicon-based sentiment methods (AFINN, Bing, NRC), we quantified polarity and discrete emotions, aggregated scores at the firm level, and applied k-means clustering to normalized emotion vectors. Results show a consistent emphasis on mission–vision–values language and a dominance of positive emotions—especially trust and anticipation. We interpret, based on cluster exemplars, that higher trust/anticipation tones can function as soft governance cues, while transparency about negatives characterizes an issue-addressing regime without eroding overall positivity. Cluster analysis reveals three stable profiles: optimistic consumer-oriented narratives, transparent issue-addressing messaging, and low-affect technical descriptions. We conclude that sentiment profiling offers a practical audit tool for aligning website copy with stakeholder expectations and governance communication, supporting benchmarking, and future tests linking narrative tone to investor behavior and firm performance. Full article

This article presents an analysis of the impact of atmospheric turbulence on the quality of images obtained during photogrammetric missions in Antarctica using a fixed-wing UAV operating in BVLOS mode. Image quality was evaluated primarily by the degree of blurring, which served as the main assessment criterion. In the Antarctic region, turbulence is a frequent phenomenon and can occur even under very light wind conditions, which formed the basis of this study. Autopilot log data were used to conduct a series of analyses, resulting in maps of areas where turbulence symptoms were recorded. In parallel, the quality of images captured during the mission was examined, producing a map of blurring levels assessed on a five-point scale. The study shows that UAV image blurring is mainly caused by sudden camera movements, mechanical vibrations from the propulsion system, and atmospheric turbulence that disrupts flight stability and overloads image stabilization. Additional factors such as low-light conditions, fog, haze, precipitation, glare, and moving shadows further reduce image clarity. Full article

Hydrogen fuel-cell-powered all-electric aircraft are promising for decarbonizing short-range aviation, but the substantial low-temperature waste heat demands a compact thermal management system (TMS). This study presents a methodological framework for the integrated co-design of the TMS and powertrain using multi-objective optimization and holistic mission-level analysis to identify optimal TMS designs and operating strategies. Changes in TMS net drag translate into changes in required aircraft thrust, while changes in powertrain, TMS, and fuel mass affect the available payload under a constant maximum take-off mass assumption. This iterative process yields performance metrics across TMS cooling architectures (parallel or series), heat exchanger mass-drag characteristics, coolant temperature targets (50, 70, or 90 °C), and installation objectives (minimizing mass or ram-air duct length). The optimal design is a parallel cooling architecture that balances mass-specific heat rejection of 4.77 kW kg⁻¹ at hot-day take-off with drag-specific heat rejection of 1.29 kW N⁻¹ at standard-day cruise. A reduction in coolant temperature at standard-day missions entails no significant performance penalties and could improve the efficiency of electrical components. A shorter ram-air duct significantly decreases the available payload by 630 kg but may facilitate nacelle integration. The findings underscore that holistic TMS-powertrain co-design and optimization is essential for rigorous design of sustainable all-electric aircraft. Full article

In the long-duration stratospheric operation of High-Altitude Platform Stations (HAPSs), strict management of the limited solar energy balance is a decisive factor determining mission success. However, existing planar approximation models ignore self-shading and incidence angle losses associated with curved surfaces. In this study, we propose a novel framework that catalogs the airframe geometry as a 4-tensor, achieving both physical rigor and computational speed. This method is a thousand times faster than ray tracing methods, and successfully reproduces the minute output fluctuations observed in actual flight data. Notably, in the winter solstice analysis, when the energy balance is most severe, the planar model overestimates power generation by approximately 25% during level flight and by approximately 12% even during turning maneuvers. Quantifying this discrepancy in environments with minimal energy margins is essential for mitigating the risk of airframe loss and formulating feasible operational plans. Full article

Digital transformation of libraries is a key driver of the development of scholarly communication, open access, and knowledge management; however, its sustainability largely depends on institutional and legal conditions. This study examines the level of legal literacy among library professionals and the institutional barriers affecting the digital transformation of academic and public libraries in the Republic of Kazakhstan. A mixed-methods research design was employed, combining a quantitative online survey of library professionals with a qualitative analysis of open-ended responses provided by library managers. The findings indicate that, despite a relatively high level of basic digital skills, legal literacy related to copyright, licensing, and open access remains insufficiently institutionalized. Significant differences were identified between academic and public libraries, reflecting variations in their institutional missions and managerial priorities. Based on the interpretation of empirical results and their comparison with international literature, the study proposes a conceptual model of digital–legal transformation of libraries that integrates digital competencies, legal literacy, and institutional support mechanisms. Additionally, a phased roadmap is developed to support the sustainable implementation of open-access practices and the development of institutional repositories within a nascent open science ecosystem. The study’s results inform the development of institutional digital strategies for libraries and contribute to the design of professional development programs for library staff. Full article

Civil registration of births and deaths underpins people’s legal identity, access to essential services, and evidence-based policy. Over the last two decades, the expansion of the National Health Mission (NHM) and the dramatic increase in institutional deliveries have created new opportunities to link maternal healthcare with critical event documentation. Primary health centres (PHCs) and community health centres (CHCs), which are frequently the initial point of contact for rural households, are emerging as important places for birthing and registration. Despite their expanding importance, the particular role of these grassroots facilities in birth registration results has not been thoroughly investigated. This study addresses that gap by assessing their role in increasing registration coverage among children under the age of five. We analyzed nationally representative data from the National Family Health Survey rounds 4 (2015–2016) and 5 (2019–2021). This study focused on children under five, examining the association between place of delivery and registration status. Descriptive analysis and multivariable logistic regression estimated the odds of registration across delivery settings. Pooled data from both survey rounds captured temporal shifts, and predicted probabilities were calculated for institutional deliveries, adjusting for socio-demographic covariates. The proportion of institutional births occurring in PHCs and CHCs rose from 30.5% to 34.7% between the two survey rounds. Registration among children delivered in these facilities increased from 80.8% to 90.2%, the highest gain among all delivery settings. Regression analysis showed that births in PHCs/CHCs were associated with 38% higher odds of being registered compared to private facilities. States designating PHCs and CHCs as official registrars, such as Delhi, Rajasthan, and Uttar Pradesh, reported the greatest improvements. Lower-level government health facilities are not only advancing safe delivery but also acting as pivotal nodes for civil registration. Their dual function creates a scalable model for integrating healthcare with legal identity creation, supporting equity and accelerating progress toward Sustainable Development Goal 16.9. Full article

Deep-sea exploration increasingly relies on Autonomous Underwater Vehicles (AUVs) to enable persistent, wide-area surveying in harsh and uncertain environments. In practice, however, deployments are constrained by tight energy budgets and bandwidth-limited, intermittent acoustic links, which complicate mission-level coordination. Moreover, many existing systems treat perception and control as loosely coupled modules, often resulting in redundant sensing, inefficient communication, and degraded overall performance—particularly under heterogeneous sensing modalities and shifting geological conditions. To address these challenges, we propose a hierarchical Federated Meta-Transfer Learning (FMTL) framework that tightly integrates collaborative perception with adaptive control for swarm optimization. The framework operates at three levels: (1) Representation Learning aligns heterogeneous sensors in a shared latent space via a physics-informed contrastive objective, substantially reducing communication overhead; (2) Meta-Learning Adaptation enables rapid transfer and convergence in new environments with minimal data exchange; and (3) Energy-Aware Control realizes closed-loop exploration by coupling Federated Explainable AI (FXAI) with decentralized multi-agent reinforcement learning (MARL) for path planning under energy constraints. Validated in high-fidelity hardware-in-the-loop simulations and a digital-twin environment, FMTL outperforms state-of-the-art baselines, achieving an AUC of 0.94 for target identification. Furthermore, an energy–intelligence Pareto analysis demonstrates a 4.5× improvement in information gain per Joule. Overall, this work provides a physically consistent and communication-efficient blueprint for the optimization and control of next-generation intelligent marine swarms. Full article

Methane is the second most important contributor to global warming, and monitoring super-emitters from space is critical for climate mitigation. Despite the advancements in hyperspectral remote sensing, comparing methane observations across diverse imaging spectrometers remains a challenging task. Different retrieval algorithms, plume segmentation techniques and uncertainty treatments make it very hard to perform fair comparisons between different products. To overcome these difficulties, this study presents HyGAS (Hyperspectral Gas Analysis Suite), a unified, open-source framework for sensor-agnostic methane retrieval and flux estimation. Starting from the established clutter-matched-filter (CMF) formalism and a physical calibration in concentration–path-length units (ppm·m), we propagate both instrument noise and surface-driven background variability consistently from methane enhancement to Integrated Mass Enhancement (IME) and flux. The framework further includes a spectrally matched background-selection strategy, scale-aware segmentation with fixed physical criteria across resolutions, and emission-rate estimation via an IME–$U_{eff}$ approach informed by Large Eddy Simulation (LES). We demonstrate the framework on near-simultaneous observations of landfills and gas infrastructure in Argentina, Turkmenistan, and Pakistan, spanning Level-1 radiance workflows (PRISMA, EnMAP, Tanager-1) and Level-2 methane products (EMIT, GHGSat). The standardised chain enables systematic inter-comparison of methane enhancement products and reduces methodological bias, supporting robust multi-mission assessment and future global monitoring. Full article