Coastal beach–dune systems along the Western Black Sea Coast represent geomorphologically complex and ecologically valuable environments that have been increasingly affected by long-term urbanisation and recreational pressure. This study examines the geomorphological settings, sedimentary connectivity and associated Natura 2000 dune habitats within two urbanised beach–dune systems, Pobeda (Burgas) and Asparuhovo (Varna), to improve their cadastral documentation and support objective conservation assessment. The analysis is based on high-resolution UAS-LiDAR surveys, complemented by UAS photogrammetry and field observations, allowing detailed three-dimensional characterisation of dune landforms, surface morphology and habitat patterns. The results identify foredune-dominated system architectures in both study areas, with the Pobeda (Burgas) and Asparuhovo (Varna) beach–dune systems comprising embryonic dunes, established foredune ridges and low-relief foredune plains, variably developed and spatially fragmented as a result of long-term urbanisation and recreational pressure, and spatially associated with dune habitats. Despite substantial anthropogenic modification, these elements remain recognisable, although locally fragmented and morphologically degraded. Subtle topographic changes related to trampling, informal access routes and surface compaction were detected, particularly affecting foredune crests and foredune plains, with implications for sediment transport continuity and habitat stability. The study shows that conventional habitat inventories alone are insufficient for capturing such changes. Integrated geomorphological and habitat analysis based on UAS-LiDAR provides a reliable framework for accurate mapping, conservation status assessment and informed consideration of coastal dune systems within the Natura 2000 network and related protection schemes.

Stabilized soil organic carbon is the most persistent fraction of soil carbon and plays a key role in long-term climate mitigation, yet its global distribution remains poorly constrained. Here we integrate georeferenced soil profiles with a machine learning model to map stabilized soil carbon in the upper one meter of soils worldwide. Global stabilized soil carbon is estimated at 1304 petagrams of carbon, representing about half of total soil carbon and concentrated in wetlands and cold-temperate regions. Soil properties explain most of the spatial variation, whereas climate and management effects show threshold responses. We further define soil negative carbon potential, the proportion of stabilized carbon in total soil carbon, as an indicator of stabilization efficiency and mitigation potential. Increasing this metric is associated with lower greenhouse gas emissions and improved economic outcomes with minimal yield trade-offs. These results provide benchmarks for Earth system models and inform soil-based climate mitigation strategies. Stabilized soil organic carbon totals 1304 pentagrams carbon globally about half of total soil carbon concentrated in wetlands and cold regions shown by mapping upper one-meter soils using georeferenced soil profiles and high precision machine learning models.

This work focuses on the investigation of ten newly synthesized spironaphthoxazines using DFT to elucidate how substituents control physicochemical behavior. Frontier-orbital analyses show substituent changes primarily shift the LUMO, controlling HOMO–LUMO gaps and electrophilicity; the open forms (MC) structures exhibit smaller gaps than closed spiro forms (SP) due to extended conjugation. Simulated IR/Raman spectra provide diagnostic markers for structural assignment. Thermodynamic parameters (S, Cp, H, G; 200–500 K) reveal higher S and Cp for MC and for longer alkyl chains, yielding lower G at elevated temperatures. Transition-state calculations indicate accessible SP↔MC isomerization barriers, confirming accessible switching. These results offer a predictive framework to position functional groups and tailor optical response, switching kinetics, and stability for responsive materials.

In whole-angle mode hemispherical resonator gyroscope (HRG) systems, time delay and damping asymmetry are critical factors affecting measurement accuracy and long-term stability. Time delay originates from signal acquisition and processing latency, resulting in misalignment between the input angular velocity and the output signal. Damping asymmetry, caused by non-uniform damping distribution within the resonator, further contributes to angle drift bias (ADB). To address these issues, this paper proposes a joint compensation method integrating cross-correlation time delay estimation with a recursive least squares algorithm. The method first estimates the system delay by analyzing the time lag between excitation and output signals, then iteratively identifies damping asymmetry parameters based on angular velocity data. Experimental results show that the proposed method reduces ADB to 1.2132°/h, representing an eightfold improvement over damping-asymmetry-only compensation (9.72°/h) and a 51.5-fold improvement compared to the uncompensated case (62.52°/h). These results underscore the non-negligible impact of time delay and the effectiveness of joint compensation in enhancing HRG performance.

The regulation of bone physiology and pathophysiology is intricately controlled by a complex interplay of cellular and molecular mechanisms. In these processes, the precise spatiotemporal coordination of biological activities in bone-resident cells plays a central role. Recently, liquid-liquid phase separation (LLPS), a mechanism underlying membraneless biomolecular condensate formation, has emerged as a transformative area of research. Liquid-liquid phase separation refers to the phase transition of biomolecules under specific conditions, leading to the formation of biomolecular condensates, which orchestrate diverse cellular functions. In this review, we provide a comprehensive synthesis of how LLPS influences bone turnover, focusing on its role in regulating bone homeostasis and its dysregulation in bone disease pathogenesis. Furthermore, aside from addressing the current challenges and limitations in this nascent field, we explore the implications of LLPS in bone regeneration, preventive strategies, and precision medicine. Despite LLPS research being in its early stages, its rapid advancement underscores its crucial role in bone biology and highlights the urgent need to integrate LLPS insights with translational approaches to advance therapeutic interventions for bone disorders.

The digitalization of vehicles has accelerated the adoption of touchscreen-based control systems and with the growing push toward full electrification of national vehicle fleets.Their combined implications for driver distraction, road safety, and the electrical infrastructure required to support large-scale vehicle electrification remain insufficiently addressed.The present study offers an essential cross-sector perspective for contemporary resilience planning by combining human-factors analysis with system-level energy considerations.This study investigates these issues by examining both the human-machine interaction demands imposed by touchscreen-centric interfaces and the energetic and infrastructural consequences of replacing all gasoline-powered passenger cars in Italy with battery electric vehicles.The methodology integrates a numerical model of driver visual distraction with empirical findings from recent eye-gaze studies.Touchscreen interactions are decomposed into phases of visual reorientation, cognitive decision-making, pointing movement, actuation, and refocusing.This framework allows estimation of total eyes-off-road time and the corresponding blind-driving distance.Model outcomes are systematically compared with measured interaction durations from controlled experimental studies.The results show that touchscreen interactions require significantly longer visual engagement than predicted by idealized human-machine interaction models, particularly for multi-step tasks such as navigation and address entry.In parallel, national fuel consumption data are used to approximate the annual distance traveled by gasoline vehicles on Italian motorways and ordinary roads.These distances are converted into electrical energy demand using representative consumption values, and the associated average and installed charging powers are computed for fast-charging, slow public charging, and universal home-charging scenarios.From an energy-system perspective, replacing all gasoline vehicles with electric vehicles would require charging power levels that exceed the current Italian peak electrical load by a wide margin, especially under a full home-charging configuration.Overall, the findings suggest that touchscreen-based interfaces lead to significant increases in driver workload, while large-scale fleet electrification imposes substantial demands on the national power system.These results underscore the need for safer interface designs and for electrification strategies that incorporate human, infrastructural, and system-level constraints.

This study examines the implications of replacing the Italian vehicle fleet with electric vehicles powered exclusively through fast and slow charging.The purpose is to quantify the additional electrical energy and peak charging power required, and to assess their compatibility with the present characteristics of major European electricity systems.The methodology combines national mobility statistics, estimated charging demand profiles, and empirical scaling factors derived from refuelling infrastructure to determine both annual energy requirements and instantaneous power needs.The analysis indicates that full fleet electrification for night-only charging would increase national electricity consumption by approximately 40-50%, a substantial yet potentially manageable rise in annual energy consumption.By contrast, the charging power needed to support large-scale fast charging reaches values close to 280 gigawatts, far exceeding the peak loads currently managed by existing transmission networks.This peak requirement is nearly five times higher than the present Italian maximum demand and surpasses, by large margins, the peak values recorded in comparable European systems.The results indicate that the principal challenge of transport electrification lies in accommodating extremely concentrated power demand within limited temporal windows.The conclusions emphasize the need for substantial upgrades to transmission and distribution networks, complemented by the widespread adoption of controlled slow charging and demand-shifting strategies that can help reduce peak loads.These findings suggest that the feasibility of large-scale vehicle electrification hinges critically on managing instantaneous power rather than total energy, underscoring the importance of coordinating infrastructure planning, regulatory frameworks, and charging behavior to ensure that electric mobility can be integrated into existing power systems without compromising stability or reliability.

This paper analyzes the design process of an aircraft propeller for a piston engine. The propeller should also damp the main critical torsional frequency of the crankshaft. The first step was the calculation of the geometrical parameters of two different blades: one according to Larrabee's procedure and the other one according to the Theodorsen's theory. The evaluation of the effect of aerodynamics and centrifugal loads has required the union of the results come from CFD (Computational Fluid Dynamics) and the ones come from the CSM (Computational Structural Mechanics), through the execution of several one way FSI (Fluid Structure Interaction) analyses. The results allowed making pre-stressed modal analyses, which gave the opportunity to identify the kinds of propeller having the fundamental frequency coincident with the main resonance frequency of the crankshaft. The final design is a blade having the deformed shape of the optimum aerodynamic design. © 2006-2015 Asian Research Publishing Network (ARPN).

Black holes (BHs), one of the most intriguing objects in the universe, can manifest themselves through electromagnetic radiation initiated by the accretion flow. Some stellar-mass BHs drive relativistic jets when accreting matter from their companion stars, forming microquasars. Non-thermal emission from the radio to teraelectronvolt gamma-ray band has been observed from microquasars, indicating the acceleration of relativistic particles. Here we report detection of four microquasars (SS 433, V4641 Sgr, GRS 1915+105, MAXI J1820+070) of spectra extending to the ultrahigh-energy (UHE; photon energy [Formula: see text] TeV) band, and one microquasar (Cygnus X-1) with a spectrum approaching 100 TeV, using the Large High Altitude Air Shower Observatory. Notably, the total emission associated with SS 433 cannot be interpreted with a single leptonic component. In the UHE band, its emission is in spatial coincidence with a giant atomic cloud, which is consistent with a hadronic origin. An elongated source is discovered from V4641 Sgr with the spectrum continuing up to 800 TeV. The detection of UHE gamma rays demonstrates that accreting BHs and their environments can operate as extremely efficient accelerators of particles up to 1 PeV, suggesting that microquasars are important contributors to Galactic cosmic rays, especially around the 'knee' region.

Deep-sea cages are highly susceptible to biofouling due to long-term seawater immersion, which promotes the attachment and growth of marine organisms on nets, significantly reducing fish survival. To address this issue, this study explores the use of low-pressure abrasive-water jets (LPAWJ) for cage fouling removal through numerical simulation. Based on a Box-Behnken response surface design, nozzle inlet pressure X1, nozzle outlet diameter X2, and target distance X3 were selected as optimization parameters. The peak jet impact force Z1, stable jet impact force Z2, peak abrasive-water jet velocity Z3, and peak abrasive particle velocity Z4 were chosen as evaluation indicators to characterize the jet’s instantaneous impact ability, sustained action ability, and dynamic particle behavior. Using the entropy method, weights for each indicator were determined, and the jet’s overall removal capability was calculated. A regression model was developed by integrating numerical simulation with the response surface methodology (RSM), and the optimal parameter combination was identified as X1 = 4.5 MPa, X2 = 10 mm, and X3 = 205.396 mm, enhancing the jet’s overall removal capability by 2.19%. The results provide theoretical support for improving LPAWJ-based cage net cleaning.