Search Results (65,733)

Thermal monocular depth estimation can provide more robust depth predictions than RGB-based methods under nighttime and adverse weather conditions. However, when trained with projected LiDAR supervision, depth models often retain structural errors in sky regions, long-range areas, and object boundaries because LiDAR measurements are sparse or missing in such regions. To address this limitation, we propose a thermal monocular depth estimation framework that incorporates propagation-based refinement. To make this refinement applicable across different base models, we further design a multi-scale feature adapter that converts heterogeneous multi-scale features with different spatial resolutions and channel dimensions into a unified representation. As a result, the same refinement architecture can be used across different base models without model-specific refiner redesign. On the multispectral stereo (MS2) dataset, the proposed method improves both BTS (big-to-small) and NeWCRFs (neural window fully connected CRFs), reducing the meter-based error metrics SqRel from 0.380 to 0.369 and RMSE from 3.163 to 3.126 for BTS, and reducing SqRel from 0.331 to 0.328 and RMSE from 2.937 to 2.924 for NeWCRFs. Qualitative results further show that the proposed method alleviates mixed-depth artifacts and abnormal depth patterns in regions lacking reliable depth supervision. Full article

The pitot tube is the core sensor for aircraft to obtain external atmospheric data, and its failure has a very important impact on flight safety. However, as its structure and principle are relatively simple, all manufacturers have not adopted available monitoring methods for its health status due to the perspective of cost and complexity reduction. The pitot tube fault warning method is conducted in this paper with a fully connected neural network (FCNN) method based on the data collected by the pitot tube itself. By constructing and selecting parameters and extracting fault features from flight record data, a pitot tube fault warning model based on an FCNN is constructed. The effectiveness of the proposed method is verified through pitot tube fault warning experiments based on actual flight record data, which can provide technical reference for pitot tube fault warning during aircraft route operation in the future. Full article

In today’s densely populated and technology-driven smart cities, natural and human-made disasters increasingly threaten the resilience of communication infrastructures, creating critical challenges for maintaining reliable connectivity. The failure of conventional networks during crises significantly hampers emergency response, coordination, and information dissemination. To address these challenges, this paper presents Weighted Average Algorithm-based Clustering and Routing (WAA-CR), a novel, secure, and adaptive UAV-based framework for disaster response and recovery. WAA-CR integrates three key components: shelters or Ground Control Stations (GCSs) as communication anchors and support hubs, survivable clustering and routing using a WAA-based metaheuristic optimizer, and secure and trustworthy drone communication enabled by a lightweight trust evaluation mechanism, and authentication model. The framework formulates a multi-objective optimization model that simultaneously minimizes the number of active UAVs and routing cost, while maximizing trust, communication reliability, and coverage. Cluster head (CH) election and routing decisions are guided by a composite fitness function that considers residual energy, link stability, mobility, and dynamic trust scores. Additionally, an adaptive maintenance mechanism enables dynamic reconfiguration to handle CH failures, trust degradation, or mobility-driven topology changes. Extensive simulations conducted in MATLAB R2020ademonstrate that WAA-CR significantly outperforms existing baseline FANET protocols in terms of energy efficiency, cluster stability, trust accuracy, and end-to-end delivery performance. These results validate the proposed framework’s effectiveness in building resilient, scalable, and secure UAV-based communication networks for post-disaster environments. Full article

Recently, cold-formed steel (CFS) structural systems have been increasingly used in building applications due to their lightweight characteristics, ease of fabrication, and efficient construction processes. Among these systems, built-up CFS columns are widely adopted to enhance load-carrying capacity; however, their axial compression behavior and failure mechanisms have not yet been fully clarified. This study aims to investigate the axial compression performance of built-up cold-formed steel columns through a combined experimental and numerical approach. This study investigates the axial compression performance of built-up cold-formed steel columns using a combined experimental and numerical approach. Following the full-scale testing of five different configurations, finite element models were developed in ABAQUS using the obtained material properties. The experimental results were used to validate and calibrate the finite element models, which provided a detailed simulation of the nonlinear structural behavior of the columns. The experimental load–displacement responses were compared with the numerical results to evaluate the accuracy of the finite element models and to identify the axial load-carrying capacity and dominant failure modes of the built-up columns. Furthermore, the tensile pull-out behavior of 3.9 mm diameter self-drilling screws utilized in the built-up column connections was examined through expedient fastener tests to facilitate a more profound understanding of the load transfer mechanism. The results highlight the influence of built-up configuration and connection behavior on the axial compression performance of CFS columns, providing practical insights for improving the design and numerical modeling of screw-connected built-up cold-formed steel column systems. Full article

We report a curious numerical observation: If atomic nuclei are modelled as connect-sums of threefoil knots with alternating chirality, the ropelength of the composite knot—a purely geometric quantity requiring no quantum mechanics—tracks the experimental binding-energy curve from hydrogen to uranium. A two-parameter fit to 50 nuclei gives $R^2=0.9998$ (coefficient of determination; 1 = perfect fit) and $\mathrm{RMS}=6.9\mathrm{MeV}$ (root-mean-square deviation between model and experiment), comparable to the five-parameter Bethe–Weizsäcker formula ($\mathrm{RMS}=8.3\mathrm{MeV}$) at less than half the parameter count. Out-of-sample predictions for ${}^{244}\mathrm{Pu}$ and ${}^{252}\mathrm{Cf}$, not used in the fit, are accurate to $0.4\mathrm{MeV}$ and $8.4\mathrm{MeV}$, respectively. What makes the observation worth reporting is not the fit itself, but the range of nuclear phenomenology that emerges uninstructed from the topology: saturation, surface energy, isospin pairing, odd-even staggering, and geometric analogues of nuclear isomers all appear as consequences of the connect-sum construction, without additional assumptions. We catalogue these correspondences, assess which are structural and which may be coincidental, and identify concrete numerical tests that would distinguish the two possibilities. Full article

One of the challenges in managing mobility in a heterogeneous network domain remains a significant challenge in Software-Defined Networking (SDN). While SDN has effectively facilitated intra-domain mobility, inter-domain mobility has been a major issue, leading to service interruptions, packet loss, and unstable communication sessions. This article presents a new concept in mobility management: a hybrid SDN-LISP network that facilitates inter-domain communication by integrating SDN with the Locator/Identifier Separation Protocol (LISP). The main idea is to introduce a new event-based orchestration model that uses OpenFlow Packet-In messages to provide instantaneous updates to Endpoint Identifiers-to-Routing Locators (EID-to-RLOC) mappings, unlike traditional LISP, which relies on timers for updates. The proposed framework has been implemented and evaluated on a Mininet-WiFi testbed under various mobility conditions. The results obtained from the experimental evaluation reveal that packet loss is reduced by 92.32% when using the proposed framework over the conventional SDN Mobility approach. Although there is a slight increase in jitter overhead due to LISP encapsulation of 0.628 ms, the framework does not compromise Transmission Control Protocol (TCP) session continuity. In addition, the control plane synchronization time is also minimized to 277.5 ms. This reveals that the proposed framework is a stable mobility solution that does not depend on any conventional IP mobility solutions and can be used in future network environments requiring seamless inter-domain connectivity. Full article

Wireless Sensor Networks (WSNs) deployed in agricultural and industrial environments require high reliability to ensure continuous monitoring and data transmission. This study presents a reliability analysis of a hybrid WSN system comprising four series-connected subsystems: (1) the central processing unit, (2) sensor nodes in cluster A, (3) sensor nodes in cluster B, and (4) communication relay units. The system operates under a k-out-of-n: G mechanism, where subsystems 2 and 3 require at least one operational unit, while subsystem 4 requires at least two. Whereas unit failures follow exponential distributions, repair processes are modeled using either general distributions or Gumbel–Hougaard copula-based approaches to capture dependencies among multiple repair units. Using Laplace transforms and supplementary variable techniques, we evaluate system reliability metrics and demonstrate that copula-based repair strategies significantly improve availability and the expected profit function. Furthermore, we propose a reduction technique governed by a factor $\rho$ that decreases component failure rates, thereby enhancing overall system reliability relative to the baseline configuration. Full article

Cascade reservoirs on the Drina River (Bosnia and Herzegovina) are heavily modified water bodies that require reliable biological tools for assessing trophic status and ecological potential. Under the Water Framework Directive (WFD), assessments of surface water ecological status and potential rely on biological quality elements, since aquatic communities integrate and respond to prevailing environmental conditions and thus serve as reliable indicators of water quality. This study aims to (i) describe phytoplankton diversity, biomass, and functional-group composition along the Drina reservoir cascade, (ii) examine monthly changes across the studied reservoirs, (iii) determine trophic status and ecological potential, and (iv) provide a preliminary estimate of total phosphorus thresholds that may support future setting of ecological potential boundaries. Phytoplankton composition and functional groups were analysed in three longitudinally connected reservoirs of the Drina River during four monthly surveys in 2024. A total of 80 phytoplankton taxa were recorded, with diatoms dominating most of the study period. The highest biomasses were recorded for Fragilaria crotonensis, Dinobryon divergens, Acanthoceras zachariasii and Sphaerocystis sp., while the dominant functional groups were P, E, A, and F. Phytoplankton assemblage structure showed moderate spatial differentiation among the reservoirs. Mean chlorophyll a and Carlson’s Trophic State Index indicated eutrophic conditions in the Višegrad Reservoir and mesotrophic conditions in the Perućac and Zvornik reservoirs, while biomass showed a pronounced summer maximum, particularly in Perućac. Ecological potential was generally classified as good or better, except for a moderate classification in the Zvornik Reservoir in late summer. The good/moderate TP boundary was estimated at 39 µg L⁻¹, linking EQR-based ecological assessment with the onset of eutrophic conditions. Overall, this study represents the first application of the phytoplankton functional group approach in cascade reservoirs in Bosnia and Herzegovina and may provide a valuable basis for the development of a phytoplankton-based monitoring framework in lakes and reservoirs, which is currently lacking. Full article

The rapid development of smart energy infrastructures and renewable energy systems requires advanced sensing solutions that provide high accuracy, expandability, and stability under real operating conditions. However, conventional gas monitoring systems are predominantly based on resistive or voltage-output sensors, which require complex analog front-end circuits and analog-to-digital conversion, leading to increased system complexity, cost, and susceptibility to electromagnetic interference. This paper tackles this limitation by proposing a frequency-domain sensing approach for multichannel monitoring of biogas plant parameters. The objective of this study is to develop and experimentally validate an extendable sensing architecture based on autogenerator microelectronic gas transducers with direct gas concentration–frequency conversion and FPGA-based digital acquisition. The proposed method is grounded in a physical–mathematical model of the space-charge capacitance of gas-sensitive semiconductor structures derived from Poisson’s equation, facilitating analytical formulation of conversion and sensitivity functions. A multichannel FPGA-based measurement system is implemented to process frequency signals without analog conditioning or ADC stages. Experimental validation was performed for CH₄ (0–85%), CO₂ (0–60%), H₂, NH₃, and H₂S (1–20,000 ppm). The results demonstrate measurement uncertainty within 0.25–0.5%, with sensitivity reaching 350–748 Hz/ppm for H₂, 455–750 Hz/ppm for NH₃, and 253–375 Hz/ppm for H₂S, while methane and carbon dioxide sensitivities reach up to 112 kHz/% and 98.7 kHz/%, respectively. Spectral analysis in the LTE-1800 band confirms improved noise immunity (up to 4.5×) and extended transmission capabilities. A 12-channel FPGA-based monitoring system (RDM-BP-1) with a 1 s sampling interval, IP67 protection, and wireless connectivity is developed and validated. The proposed architecture eliminates analog signal conditioning, reduces hardware complexity, and provides an easily expandable and reliable sensing solution for smart buildings, renewable energy systems, and cloud-integrated energy infrastructures. Full article

Targeting the “Fishtailing Effect” associated with shallow-water, pile-founded column single point mooring (SPM) systems, this study investigates the vessel’s motion characteristics under multiple operational scenarios using a numerical calculation method validated by model tests. A refined classification of combined wind, wave, and current conditions was conducted. The study examines the vessel’s sway and mooring line tension response under both collinear and non-collinear combinations of these environmental forces. Furthermore, methods for suppressing vessel motion were explored. The results indicate that vessel motion leading to the “Fishtailing Effect” is more prone to occur under collinear wind, wave, and current conditions. Wave and wind energy can, to some extent, mitigate the vessel motion. When the current speed exceeds a certain critical threshold, the extreme values of the mooring forces on the swaying vessel undergo an abrupt change. Applying a stern tug force and reducing the mooring line length are both effective in decreasing the vessel motion range and the tension in the mooring lines. The findings shed light on the fishtailing-effect characteristics of tankers moored at pile-founded column SPM systems, providing a valuable reference for the safety and stability design of such mooring systems. Full article

The sixth-generation (6G) mobile networks are envisioned to deliver seamless three-dimensional(3D) coverage from ground to sky and vice versa. In parallel, aerial corridors are emerging to elevate ground-based transportation into the air, enabling smart air mobility for unmanned aerial vehicles (UAVs). The convergence of this intelligent transportation system (ITS) with 6G introduces new challenges: how to ensure reliable, efficient connectivity within aerial corridors, and how these corridors can serve as foundational sky infrastructure to advance the 6G ecosystem. This paper presents a comprehensive survey that systematically presents aerial corridors as integrated 6G sky infrastructure, unifying corridor geometry, network architecture, channel modeling, and key enabling technologies within a single framework. It conceptualizes the aerial corridor as a tube-shaped, multi-lane, bidirectional structure to manage drone-based roles, including user equipment (UE), base stations (BS), and communication relays. To support this vision, key enablers such as air-to-ground channel modeling and integrated sensing and communication (ISAC) are investigated. The proposed infrastructure aligns with the IMT-2030 vision, supporting machine-type communication, ubiquitous connectivity, and immersive services in regulated aerial space. Full article

The world of Star Wars may seem far removed from Renaissance England, but through an examination of the regnal aspects of Henry VIII and (Emperor) Sheev Palpatine (Darth Sidious), it is evident that their ruling styles, concerns, and personal characteristics are quite similar. Specifically, they share (1) a connection to the arts through visual, architectural, and political themes, making them ‘Renaissance men’; (2) a fixation with male (Force-sensitive) bloodlines, whether through biological children or Sith Apprentices; and (3) a legacy of having their most powerful and ‘best’ heirs being women—Elizabeth I (r. 1558–1603) and Rey (Palpatine/Skywalker). Hence, these case studies, which rely on the trait approach of leadership, demonstrate the utility of comparing leaders from different times, cultures, and realities in an effort to understand not only good and bad leadership elements, but also the nature of leaders’ downfalls. Full article

Mountain flood susceptibility in complex mountainous basins is strongly influenced by terrain–climate interactions; however, the linkage between spatial susceptibility patterns and hydrological processes remains poorly understood. This study proposes a process-oriented framework that explicitly links flood susceptibility patterns with hydrological processes, moving beyond conventional approaches that rely on independent model integration. The Baishuijiang River Basin, located in Wenxian County, southern Gansu Province, China, is selected as a representative mountainous watershed for this analysis. The specific conclusions are as follows: (1) Flood susceptibility was mapped using a Particle Swarm Optimization (PSO)-enhanced Maximum Entropy (MaxEnt) model based on multi-source environmental variables, including climatic, terrain, soil, land cover, and vegetation factors. The model achieved high predictive accuracy (Area Under the Receiver Operating Characteristic Curve (AUC) = 0.912), identifying precipitation of the driest month (bio14), elevation, and land use as dominant controlling factors. Medium-to-high-susceptibility areas account for approximately 22% of the basin and are mainly distributed along river valleys and flow convergence areas. These patterns are strongly associated with reduced infiltration capacity under dry antecedent conditions and enhanced flow concentration in steep terrain, and they exhibit clear nonlinear responses and threshold effects. (2) Hydrological simulations using Hydrologic Engineering Center–Hydrologic Modeling System (HEC-HMS) show good agreement with observed runoff (Nash–Sutcliffe Efficiency (NSE) = 0.74−0.85). Sensitivity analysis indicates that runoff dynamics are primarily controlled by the Curve Number (CN), recession constant, and ratio to peak, corresponding to infiltration capacity, recession processes, and peak discharge amplification. The spatial consistency between high-susceptibility areas and areas of strong runoff response demonstrates that susceptibility patterns can be physically explained through hydrological processes, providing a process-based interpretation rather than a purely statistical prediction. (3) Future projections indicate that medium–high-susceptibility areas remain generally stable but show a gradual expansion (+5.2% ± 0.8%) and increasing concentration along river corridors under climate change scenarios. This reflects intensified precipitation variability and enhanced runoff concentration processes, suggesting a climate-driven amplification of flood risk in hydrologically connected areas. Overall, this study goes beyond conventional susceptibility assessment by establishing a physically interpretable framework that provides a consistent linkage between environmental controls, susceptibility patterns, and hydrological responses. The proposed approach is transferable to similar mountainous basins with strong terrain–climate interactions, although uncertainties related to data limitations and single-basin application remain and require further investigation. Full article

Agrivoltaics (AV) has emerged as an integrated land-use innovation capable of simultaneously addressing food, energy, and water challenges, yet its systemic implications for farming system sustainability remain insufficiently synthesized. This review adopts a farming system dynamics perspective to examine how AV systems reorganize biophysical, ecological, and socio-economic interactions across agroecosystems. Drawing upon agroecological principles, pathways of sustainable intensification and ecological intensification, and resource-loop strategies in circular economy, we identify the key elements and cause-and-effect relationships that shape AV system performance. Evidence indicates that the co-location of photovoltaics (PV) structures and crop cultivation generates new system properties, altered light distribution, moderated microclimates, redistributed soil moisture, and diversified production functions that influence productivity, resource-use efficiency, ecological services, and farm resilience. Using causal loop analysis, we conceptualize four central feedback dynamics: (i) PV–crop trade-offs and spatial-sharing relationships; (ii) microclimate modifications and crop physiological responses; (iii) ecological performance and landscape-level interactions; and (iv) circularity loops connecting resource conservation, renewable-energy substitution, soil processes, and material flows. This feedback collectively determines eco-efficiency outcomes, including enhanced land-equivalent productivity, improved water-use efficiency, strengthened regulating services, and reductions in external energy dependence. At the farming-system scale, AV diversifies income streams and stabilizes yields under climatic variability, whereas at the landscape scale, it fosters multifunctionality by supporting regenerative resource flows and ecological resilience. Building on these insights, we propose an integrated framework that links agroecological elements with dynamic feedback structures to guide context-specific AV design, management, and governance. This system-oriented synthesis provides a foundation for future research and policy efforts aimed at optimizing AV as a circular, resilient, and sustainable farming system innovation. Full article

The use of renewable energy sources instead of conventional ones, together with the development of efficient electricity storage solutions, represents a central objective of the transition to sustainable and resilient energy systems. In this context, two main development directions are the integration of hydrogen in the energy chain (Power-to-Gas) and the use of batteries, each with specific advantages and disadvantages, compared to internal combustion engines. The purpose of this work was to evaluate the dynamic response time of a hydrogen fuel cell model powered by green hydrogen, under conditions of sudden and instantaneous power demand, for its integration into wind-based renewable energy systems. Experimental research was carried out on an autonomous installation designed to operate continuously for an unlimited duration, simulating the integration of hydrogen produced from wind sources. The novelty consists of the application of an instrumental method for automatic measurement of the response time of a proton exchange membrane hydrogen fuel cell, based on the automatic acquisition and processing of measured electrical signals. The response time of the fuel cell was compared with that of an internal combustion engine based on the classic Carnot cycle, using a dedicated oscilloscope. The load connection time, the current and voltage variation as a function of time were recorded simultaneously. The results show that the response time of the fuel cell is relatively short (approximately 0.3 ms), much lower than that of the internal combustion engine (0.7 s), being of the order of about 2333 times smaller. In conclusion, the hydrogen fuel cell can be effectively integrated into renewable energy systems for the role of an uninterruptible power supply, with an exceptionally fast dynamic response, suitable for applications in regulating and supporting wind-powered networks. Full article