Search Results (582)

This study applies spectral analysis and singular spectrum analysis (SSA) to mean annual runoff of the Dniester River for 1950–2024 to identify dominant periodic components governing the hydrological regime of this transboundary basin shared by Ukraine and Moldova. The novelty lies in a basin-specific integration in the first systematic application of a combined spectral–SSA framework to the Dniester River, enabling consistent characterization of runoff variability and assessment of large-scale natural drivers. Time series from three gauging stations are analysed to develop data-driven runoff models and medium-term forecasts. Four stable groups of periodic variability are identified, with characteristic timescales of approximately 30, 11, 3–5.8, and 2 years, corresponding to major atmospheric–oceanic oscillations (AMO, NAO, PDO, ENSO, QBO) and the 11-year solar cycle. Cross-spectral and coherence analyses reveal a statistically significant relationship between solar activity and river discharge, with an estimated lag of about 2 years. SSA reconstructions explain more than 80% of discharge variance, indicating high model reliability. Forecast comparisons show that spectral methods tend to amplify long-term trends, CNN–LSTM models produce conservative trajectories, while a hybrid ensemble approach provides the most balanced and physically interpretable projections. Ensemble forecasts indicate reduced runoff during 2025–2028, followed by recovery in 2029–2034, supporting long-term water-resources planning and climate adaptation. Full article

The historical and conceptual foundations of General Relativity are revisited, putting the main focus on the physical meaning of the invariant $d{s}^2$, the Equivalence Principle, and the precise interpretation of spacetime geometry. It is argued that Albert Einstein initially sought a dynamical formulation in which $d{s}^2$ encoded the gravitational effects, without invoking curvature as a physical entity. The now more familiar geometrical interpretation—identifying gravitation with spacetime curvature—gradually emerged through his collaboration with Marcel Grossmann and the adoption of the Ricci tensor in 1915. Anyhow, in his 1920 Leiden lecture, Einstein explicitly reinterpreted spacetime geometry as the state of a physical medium—an “ether” endowed with metrical properties but devoid of mechanical substance—thereby actually rejecting geometry as an independent ontological reality. Building upon this mature view, gravitation is reconstructed from the Weak Equivalence Principle, understood as the exact compensation between inertial and gravitational forces acting on a body under a uniform gravitational field. From this fundamental principle, together with an extension of Fermat’s Principle to massive objects, the invariant $d{s}^2$ is obtained, first in the static case, where the gravitational potential modifies the flow of proper time. Then, by applying the Lorentz transformation to this static invariant, its general form is derived for the case of matter in motion. The resulting invariant reproduces the relativistic form of Newton’s second law in proper time and coincides with the weak-field limit of General Relativity in the harmonic gauge. This approach restores the operational meaning of Einstein’s theory: spacetime geometry represents dynamical relations between physical measurements, rather than the substance of spacetime itself. By deriving the gravitational modification of the invariant directly from the Weak Equivalence Principle, Fermat Principle and Lorentz invariance, this formulation clarifies the physical origin of the metric structure and resolves long-standing conceptual issues—such as the recurrent hole argument—while recovering all the empirical successes of General Relativity within a coherent and sound Machian framework. Full article

The valuation of companies has long been a cornerstone of financial analysis and investment decision-making, offering critical frameworks for investors to gauge a firm’s worth and evaluate the relative value of future income streams within a specific industry or sector. In this work we propose a new valuation framework by integrating traditional and modern valuation approaches, providing actionable insights for investors and analysts seeking to optimize asset allocation and portfolio performance. We introduce a novel framework (TARFA) to comparable company valuation by identifying investor-preferred return-driving points for accounting-based factors. Through an analysis of 68 commonly used accounting measures, the study identifies three key factors that drive superior returns. The results of the TARFA framework demonstrate that both general and sector-specific models consistently outperformed population returns, with the general model showing superior performance in broader market contexts. The study also highlights the stability of key financial ratios over time and introduces the Relative Equity Score, further enhancing the model’s ability to identify undervalued equities. Full article

Electrical strain gauges are essential for monitoring wind turbine tower loads and fatigue, but accurate load measurements from these sensors require calibration over time to correct the zero-drift found in long-term measured signals. Calibration is often performed using nacelle rotation events for cable untwisting, where the tower mechanical load is known; however, non-uniform solar heating during these events can introduce thermal stresses that are misinterpreted as drift, causing systematic errors. This study evaluates six preprocessing methods for correcting zero-drift and thermal stresses in strain gauges, using measurements from two tower cross-sections—one with temperature sensors and one without. Performance is quantified using the scatter of the 10 min mean bending moments in the fore–aft and side-to-side directions and the cumulative fatigue damage over the monitoring periods. Results show that modelling the thermal stresses using a linear regression model with temperature measurements as inputs yields the most physically consistent load curves. If temperature measurements are unavailable, the effects of thermal stresses can be partly mitigated by restricting calibration to nighttime events or using solar-position variables in a regression model (instead of temperatures). As expected, the choice of preprocessing method significantly impacts load curves, but its influence on fatigue damage estimates is limited. Full article

Flexible strain sensors capable of conformal integration with living organisms are essential for advanced wearable electronics, human–machine interaction, and plant health. However, many existing sensors require complex fabrication or rely on non-breathable elastomer substrates that interfere with the physiological microenvironment of skin or plant tissues. Here, we present a low-cost, breathable, and highly stretchable strain sensor constructed from biomedical materials, in which a double-layer medical elastic bandage serves as the porous substrate and an intermediate conductive medical elastic tape impregnated with carbon nanotubes (CNTs) ink acts as the sensing layer. Owing to the hierarchical textile porosity and the deformable CNTs percolation network, the sensor achieves a wide strain range of 100%, a gauge factor of up to 2.72, and excellent nonlinear second-order fitting (R² = 0.997). The bandage substrate provides superior air permeability, allowing long-term attachment without obstructing moisture and gas exchange, which is particularly important for maintaining skin comfort and preventing disturbances to plant epidermal physiology. Demonstrations in human joint-motion monitoring and real-time plant growth detection highlight the device’s versatility and biological compatibility. This work offers a simple, low-cost yet effective alternative to sophisticated strain sensors designed for human monitoring and plant growth monitoring, providing a scalable route toward multifunctional wearable sensing platforms. Full article

In ultrafast science, the strong-field approximation (SFA) provides a powerful framework to describe high-order harmonic generation (HHG) and related phenomena. Meanwhile, within the current ab initio theoretical framework, the use of nonlocal potentials in calculating multi-electron molecular wave functions is almost unavoidable. We find that when such wave functions are directly applied to compute transition dipole moments for correcting SFA, it introduces a fundamental gauge transformation problem. Specifically, the nonlocal potential contributes an additional gauge-dependent phase function to the dipole operator, which directly modifies the phase of the transition dipole. As a consequence, the saddle-point equations acquire an entirely different structure compared to the standard SFA, leading to a splitting of the conventional short and long classical trajectories in HHG into multiple distinct quantum trajectories. Here, “complex molecules” refers to multi-center molecular systems whose nonlocal electronic structure leads to gauge-dependent strong-field responses. Our analysis highlights that the validity of gauge in-variation cannot be assumed universally in SFA framework. Our approach combines the molecular strong-field approximation with gauge transformation analysis, incorporating nonlocal pseudopotentials, saddle-point equations, and multi-center recombination effects. Full article

Deflection slopes measured by the traffic speed deflectometer (TSD) are being used to backcalculate the moduli of pavement layers. Pavement surface roughness causes variations in tyre load magnitude due to excitation, which affects TSD measurements. In this study, three rough pavement surface profiles over 150 m longitudinal distances were extracted from the Long-Term Pavement Performance (LTPP) programme database. Utilising finite element method (FEM) simulation of the TSD pass at a travel speed of 80 km/h over a three-layer flexible pavement system containing the rough surface profiles and employing the Greenwood Engineering TSD backcalculation tool, it was found that tyre load excitation can lead to backcalculation errors of up to 48%. By obtaining deflection slopes at equal distance intervals along the 150 m pavement profiles, it was found that averaging the deflection slopes across 9 measurement points reduced backcalculation errors to 10%, while increasing the number of measurement points to 28 further lowered the backcalculation errors to 5%. These findings highlight the potential to mitigate the effects of tyre load excitation on TSD backcalculation outputs without relying on strain gauges, which are mounted on modern TSDs to measure instantaneous tyre load magnitudes but are sensitive to environmental conditions and require calibration. Full article

Distributed fiber-optic sensing (DFOS) with intentionally spaced mechanical fixity points was experimentally evaluated for the structural health monitoring (SHM) of reinforced concrete (RC) members. A full-scale four-point bending test was conducted on a 12 m RC beam (400 × 400 mm) instrumented with a single-mode DFOS cable incorporating internal anchors at 2 m intervals and bonded externally with structural epoxy. Brillouin time-domain analysis (BOTDA) provided distributed strain measurements at approximately 0.5 m spatial resolution, with all cables calibrated to ±15,000 µε. Under stepwise monotonic loading, the system captured smooth, repeatable strain baselines and clearly resolved localized tensile peaks associated with crack initiation and propagation. Long-gauge averages exhibited a near-linear load–strain response (R² ≈ 0.99) consistent with discrete foil and vibrating-wire strain gauges. Even after cracking, the DFOS signal remained continuous, while some discrete sensors showed saturation or scatter. Temperature compensation via a parallel fiber ensured thermally stable interpretation during load holds. The fixed-point configuration mitigated local debonding effects and yielded unbiased long-gauge strain data suitable for assessing serviceability and differential settlement. Overall, the results confirm the suitability of fixed-point DFOS as a durable, SHM-ready sensing approach for RC foundation elements and as a dense data source for emerging digital-twin frameworks. Full article

Understanding the temporal variation in streamflow in the Lancang–Mekong River and its driving mechanism is essential for water resource management of this important international river. In this study, streamflow at the Chiang Saen gauging station was simulated using a long short-term memory (LSTM) model driven by satellite-based Multi-Source Weighted-Ensemble Precipitation (MSWEP) and Multi-Source Weather (MSWX) datasets, with the aim of quantifying the contributions of climate change and human activities to streamflow variations. A key contribution of this work lies in the use of LSTM to reproduce naturalized streamflow conditions—using only climate inputs—thereby providing a data-driven alternative to conventional process-based modeling approaches in this data-scarce basin. The monthly precipitation and temperature data of Chiang Saen station from 1979 to 1991 are used for model training and validation. The natural streamflow of Chiang Saen station from 1992 to 2021 is reconstructed based on the trained model. The results show that the annual average precipitation of the basin from 1979 to 2021 only exhibits a statistically insignificant decreasing trend, while the annual average temperature shows a statistically significant upward trend, and the inter-annual variation in the annual average streamflow shows a non-significant downward trend. Periodic analysis shows that the main periodicity of precipitation, temperature, and streamflow data is 12 months, following annual periodicity in climate. LSTM simulations demonstrate high accuracy in predicting the streamflow in T month based on the MSWEP precipitation and MSWX temperature data in T-2, T-1, and T months. On an annual scale, the streamflow in the changing period (1992–2021) decreases by only 4.6% compared with the reference period (1979–1991). In spring, the streamflow in the changing period is 30.6% higher than that of the reference period, and climate change and human activities contribute 40.8% and 59.2%, respectively. Increases in streamflow (3.4%) are also detected in the winter, with human activity as the dominant contributing factor. For the summer, the streamflow in the changing period is −8.2% lower than that in the reference period, with a greater contribution from human activities (68.7%) than climate change (31.3%). The streamflow in autumn of the changing period is −12.1% lower than that in the reference period, with a greater contribution from human activities (90.2%) than climate change (9.8%). In general, the findings of this study indicate that the driving mechanisms behind streamflow changes at Chiang Saen are complex at different temporal scales, and they provide valuable insights for improving our understanding of hydrological changes within the Lancang–Mekong River Basin. Full article

Reliable in situ quantification of interlayer mechanics in CRTS-II ballastless track slabs remains limited by the poor instrumentability of the CA mortar layer. This study implements a quasi-distributed fiber-optic sensing scheme by encapsulating FBGs in PVC conduits and embedding them within the CA mortar to track strain evolution under vertical loading. Four 1:3 scaled slabs were tested using stepwise load control (200 kN per step) to failure, and fiber measurements were cross-validated against conventional strain gauges on the reinforcement. The two systems showed consistent load–strain trends, while the fiber approach exhibited near-zero baseline offset and higher temporal resolution, enabling detection of small-amplitude strain changes that the gauges missed. The CA mortar displayed a clear tension-to-compression transition with increasing load; with two vertical rebars the ultimate load of the mortar layer reached 1400 kN, representing a 75% improvement over the rebar-free configuration and delaying compressive crushing through enhanced interlayer cooperation. Increasing the rebar diameter further restrained deformation and elevated the load level at which the transition occurred. The results demonstrate a practical interlayer monitoring route for CA mortar and quantify the strengthening role of vertical rebars, offering actionable guidance for design optimization and long-term condition assessment of CRTS-II slab tracks. Full article

Accurate streamflow forecasting is crucial for water resources management and flood mitigation, yet it remains challenging due to the complex dynamics of hydrological systems. Conventional data-driven approaches often struggle to effectively capture spatio-temporal evolution characteristics, particularly the dynamic interdependencies among streamflow gauges. This study proposes a novel deep learning architecture, termed DynaSTG-Former. It employs a multi-channel dynamic graph constructor to adaptively integrate three spatial dependency patterns: physical topology, statistical correlation, and trend similarity. A dual-stream temporal predictor is designed to collaboratively model long-range dependencies and local transient features. In an empirical study within the Delaware River Basin, the model demonstrated exceptional performance in multi-step-ahead forecasting (12-, 36-, and 72 h). It achieved basin-scale Kling–Gupta Efficiency (KGE) values of 0.961, 0.956, and 0.855, significantly outperforming baseline models such as LSTM, GRU, and Transformer. Ablation studies confirmed the core contribution of the dynamic graph module, with the Pearson correlation graph playing a dominant role in error reduction. The results indicate that DynaSTG-Former effectively enhances the accuracy and stability of streamflow forecasts and demonstrates its strong robustness at the basin scale. It thus provides a reliable tool for precision water management. Full article

This paper investigates the validity of the long wavelength approximation in the calculation of two-photon decay of $2s_{1/2}$ level in hydrogen-like ions with nuclear charge $Z=1-100$ based on time-dependent second-order perturbation theory and angular momentum algebra. While the relativistic structure effects on the two-photon decay rates are highlighted in the literature, the role of slowing effects in the photon electric dipole operators are not discussed extensively. The rate is computed by the sum-over-states method, with bound-bound and bound-free electric dipole matrix elements obtained in the Babushkin and Coulomb gauges, which satisfy the Lorenz gauge condition, as well as their non-relativistic limits in the long-wavelength approximation (Length and Velocity forms, respectively). The present results explicitly show how this approximation breaks gauge invariance by overestimating the Babushkin values by ∼24%${\left(\alpha Z\right)}^2$ while underestimating the Coulomb rates by ∼$31\%{\left(\alpha Z\right)}^2$. Using analytical eigenfunctions of the Dirac equation, we found that the contributions of the negative continuum states to the rate scale are ∼$0.0134{\left(\alpha Z\right)}^4$ in the Babushkin gauge and ∼$1.46{\left(\alpha Z\right)}^4$ in the Coulomb gauge, making the latter gauge more susceptible to errors when attempting to achieve basis completeness in multiphoton calculations. The present results are useful in assessing the complexity requirements of radiative transition rates for atomic systems of interest. Full article

Conductive hydrogels are ideal for flexible strain sensors, yet their practical use is often limited by water evaporation, signal hysteresis, and structural instability, which impair linearity, durability, and long-term reliability. To overcome these challenges, we developed a robust multiple-network hydrogel composed of poly(vinyl alcohol) (PVA), polyacrylic acid (PAA), in situ polymerized polyaniline (PANi), and the ionic liquid [EMIM][TFSI]. The resulting composite exhibits an exceptional linear piezoresistive response across its entire working range—from rest to fracture strain of 290%—together with high conductivity (0.68 S/cm), fast response/recovery (0.34 s/0.35 s), and a maximum gauge factor of 2.78. Mechanically robust (tensile strength ≈ 3.7 MPa, modulus ≈ 1.3 MPa), the hydrogel also demonstrates outstanding cyclic durability, withstanding over 12,000 stretching–relaxation cycles, and markedly improved dehydration resistance, retaining about 60% of its mass after 3 days at room temperature. This work provides a holistic material solution for developing high-performance, reliable strain sensors suitable for wearable electronics and soft robotics. Full article

Understanding suspended sediment transport in macrotidal embayments is crucial for assessing water quality, ecosystem function, and long-term morphological stability. This study provides a high-resolution, localized estimate of suspended sediment flux and examines the empirical relationship between turbidity (NTU, nephelometric turbidity unit) and total suspended matter (TSM, mg·L⁻¹) in the main tidal channel of Gomso Bay, a UNESCO-designated tidal flat on the west coast of Korea. A 13 h high-resolution fixed-point observation was conducted during a semi-diurnal tidal cycle using a multi-instrument platform, including an RCM, CTD profiler, tide gauge, and water sampling for gravimetric TSM analysis. Vertical measurements at the surface, mid, and bottom layers, taken every 15–30 min, revealed a strong linear correlation (R² = 0.94) between turbidity and TSM, empirically validating the use of optical sensors for real-time sediment monitoring under the highly dynamic conditions of Korean west-coast tidal channels. The net suspended sediment transport load was estimated at approximately 5503 kg·m⁻¹, with ebb-dominant residual currents indicating a net seaward sediment flux at the observation site. Residual flows over macrotidal channels are known to vary laterally, with landward fluxes often occurring over shoals. Importantly, the results from this single-station, short-duration observation indicate a predominantly seaward suspended sediment transport during the study period, which should be interpreted as a localized and time-specific estimate rather than a bay-wide characteristic. Nevertheless, these findings provide a baseline for assessing sediment flux and contribute to future applications in digital twin modeling and coastal management. Gomso Bay is part of the UNESCO-designated ‘Getbol, Korean Tidal Flats’, underscoring the global significance of preserving and monitoring this dynamic coastal system. Full article

In China, food security has long held a critical strategic position. Conducting research on the interconnections between People–Land–Food (P-L-F) is of significant importance for promoting the efficient use of resources and ensuring national food security. In this research, we utilize the entropy weighting technique coupled with an integrated adaptability assessment framework to gauge the composite development and adaptability indices of the P-L-F nexus in Xinjiang over the two-decade period from 2000 to 2020. Furthermore, we apply a barrier analysis model to identify impediments to the harmonious and adaptive progression of this intricate system. Results indicate the following: ① From 2000 to 2020, Xinjiang’s P-L-F system grew at an average annual rate of 1.39%, with people, land, and food subsystems increasing by 0.32%, 1.99%, and 1.9%, respectively. ② Regional adaptability varied significantly—southern Xinjiang improved over time, while the north remained higher overall; dual subsystems showed steady enhancement. ③ The people subsystem’s barrier intensity increasingly outpaced that of the food subsystem, highlighting that the dynamics between people and land emerged as the primary constraints on the harmonious and adaptive evolution of the P-L-F nexus. The study offers insights into P-L-F coordination and sustainable development in arid regions. Full article