Search Results (6,211)

Background: Quantitatively detecting whether plants exhibit measurable bioelectric differences in the presence of nearby human movement remains challenging, in part because plant signals are low-amplitude, slow, and easily confounded by environmental factors. Methods: We recorded bioelectric activity from 2978 plant samples across three species (basil, salad, tomato) using differential electrode pairs (leaf and soil electrodes) sampling at 142 Hz. Two trained performers executed three specific eurythmic gestures near experimental plants while control plants remained isolated. Random Forest and Convolutional Neural Network classifiers were applied to distinguish the control from treatment conditions using engineered features including spectral, temporal, wavelet, and frequency domain characteristics. Results: Random Forest classification achieved 62.7% accuracy (AUC = 0.67) distinguishing differences in recordings collected near a moving human from control conditions, representing a statistically significant 12.7 percentage point improvement over chance. Individual performer signatures were detectable with 68.2% accuracy, while plant species classification achieved only 44.5% accuracy, indicating minimal species-specific artifacts. Temporal analysis revealed that the plants with repeated exposure exhibited consistently less negative bioelectric amplitudes compared to single-exposure plants. Innovation: We introduce a data-driven approach that pairs standardized, short-window bioelectric recordings with machine-learning classifiers (Random Forest, CNN) to test, in an exploratory manner, whether plant signals differ between human-moving-nearby and isolation conditions. Conclusions: Plants exhibit modest but statistically detectable bioelectric differences in the presence of nearby human movement. Rather than attributing these differences to eurythmic movement itself, the present design can only demonstrate that plant recordings collected within ~1 m of a moving human differ, modestly but statistically, from recordings taken ≥3 m away. The underlying biophysical pathways and specific contributing factors (airflow, VOCs, thermal plumes, vibration, electromagnetic fields) remain unknown. These results should therefore be interpreted as exploratory correlations, not mechanistic evidence of gesture-specific plant sensing. Full article

Benford’s Law, also known as the First-Digit Law, describes the non-uniform distribution of leading digits in many naturally occurring datasets. This phenomenon can be observed in data such as financial transactions, tax records, or demographic indicators, but the application of Benford’s Law to data from the field of transport infrastructure remains largely underexplored. As interest in using statistical distributions to identify spatial and regional patterns grows, this paper explores the applicability of Benford’s Law to anthropogenic geographic data, particularly whether the lengths of higher-level segments of the main road network across European Union member states follow Benford’s Law. To evaluate the conformity of the data from all European Union countries with Benford’s distribution, Pearson’s ${\chi }^2$ test of association, the p-value, and the Kolmogorov–Smirnov test were used. The results consistently show low ${\chi }^2$ values and high p-values, indicating a strong agreement between observed and expected distributions. The relationship between the distribution of higher-level segment lengths and the leading digits of these lengths was studied as well. The findings suggest that the length distribution of the main road networks’ higher-level segments closely follows Benford’s Law, emphasizing its potential as a simple yet effective tool for assessing the reliability and consistency of geographic and infrastructure datasets within the European context. Full article

This research presents a comprehensive analysis of the spatial extent and temporal change in benthic habitats within the Puck Lagoon in the southern Baltic Sea, utilizing integrated machine learning classification and multi-sourced remote sensing. Object-based image analysis was integrated with Random Forest, Support Vector Machine, and K-Nearest Neighbors algorithms for benthic habitat classification based on airborne bathymetric LiDAR (ALB), multibeam echosounder (MBES), satellite bathymetry, and high-resolution aerial photography. Ground-truth data collected by 2023 field surveys were supplemented with long temporal datasets (2010–2023) for seagrass meadow analysis. Boruta feature selection showed that geomorphometric variables (aspect, slope, and terrain ruggedness index) and optical features (ALB intensity and spectral bands) were the most significant discriminators in each classification case. Binary classification models were more effective (93.3% accuracy in the presence/absence of Zostera marina) compared to advanced multi-class models (43.3% for EUNIS Level 4/5), which identified the inherent equilibrium between ecological complexity and map validity. Change detection between contemporary and 1957 habitat data revealed extensive Zostera marina loss, with 84.1–99.0% cover reduction across modeling frameworks. Seagrass coverage declined from 61.15% of the study area to just 9.70% or 0.63%, depending on the model. Seasonal mismatch may inflate loss estimates by 5–15%, but even adjusted values (70–94%) indicate severe ecosystem degradation. Spatial exchange components exhibited patterns of habitat change, whereas net losses in total were many orders of magnitude larger than any redistribution in space. These findings recorded the most severe seagrass habitat destruction ever described within Baltic Sea ecosystems and emphasize the imperative for conservation action at the landscape level. The methodology framework provides a reproducible model for analogous change detection analysis in shallow nearshore habitats, creating critical baselines to inform restoration planning and biodiversity conservation activities. It also demonstrated both the capabilities and limitations of automatic techniques for habitat monitoring. Full article

In marine seismic exploration, ghost waves distort reflection waveforms and narrow the frequency band of seismic records. Traditional deghosting methods are susceptible to practical limitations from sea surface fluctuations and velocity variations. This paper proposes a τ-p domain deghosting method based on the Hybrid Least Squares Residual (HyBR LSMR) algorithm. We first establish a linear forward model in the τ-p domain that describes the relationship between the total wavefield and upgoing wavefield, transforming deghosting into a linear inverse problem. The method then employs the hybrid LSMR algorithm with Tikhonov regularization to address the inherent ill-posedness. A key innovation is the integration of the Generalized Cross Validation (GCV) criterion to adaptively determine regularization parameters and iteration stopping points, effectively avoiding the semi-convergence phenomenon and enhancing solution stability. Applications to both synthetic and field data demonstrate that the proposed method effectively suppresses ghost waves under various acquisition conditions, significantly improves the signal-to-noise ratio and resolution, broadens the effective frequency band, and maintains good computational efficiency, providing a reliable solution for high-precision seismic data processing in complex marine environments. Full article

Accurate subsurface velocity modeling is of fundamental scientific and practical significance for seismic data processing and interpretation. However, conventional depth-domain methods still face limitations in physical consistency and inversion accuracy. To overcome these challenges, this study proposes a deep learning-based seismic velocity modeling approach in the time domain. The method establishes an end-to-end mapping between seismic records and velocity models directly in the time domain, reducing the nonlinear complexity of mapping time-domain data to depth-domain models and improving prediction stability and accuracy. Synthetic aquifer velocity models were constructed from representative stratigraphic features, and multi-shot seismic records were generated through forward modeling. A U-Net network was employed, taking multi-shot seismic records as input and time-domain velocity fields as output, with training guided by a mean squared error (MSE) loss function. Experimental results show that the proposed strategy outperforms conventional depth-domain approaches in aquifer structure identification, velocity recovery, and interlayer contrast depiction. Quantitatively, significant improvements in MSE, peak signal-to-noise ratio, and structural similarity index indicate higher reconstruction reliability. Overall, the results confirm the effectiveness and potential of the proposed time-domain framework for aquifer velocity inversion and its promise for intelligent seismic velocity modeling. Full article

An experimental technique was developed for two-dimensional Particle Image Velocimetry (PIV) measurement of wall shear flow around a bubble growing under dissolved gas supersaturation. Carbonated water was used as dissolved-gas-supersaturated liquid, and its flow was created in a small container with a tube pump. An isolated CO₂ bubble nucleated from an intentionally created scratch on the glass surface was placed in the flow. The mass-diffusion-driven growth of the bubble (from nucleation to detachment from the surface) was recorded using a video camera with backlighting; the radius of the detached bubble was below 1 mm in the present experimental conditions. The velocity field without and with the wall-attached bubble was obtained through PIV with the water (seeded with fluorescent particles) and with a planar laser sheet, which enables one to obtain local shear flow. With the measured liquid velocity at the bubble center, the particle Reynolds number was found to be below 1. The proposed PIV measurement technique allows for careful examination of bubble detachment dynamics and convective mass transfer around attached bubbles. Full article

Forest damage has been increasingly recorded over the past decade in both Europe and Hungary, primarily due to prolonged droughts, causing a decline in forest health. In the framework of ICP Forests, the forest damage has been monitored for decades; however, it is labour-intensive and time-consuming. Satellite-based remote sensing offers a rapid and efficient method for assessing large-scale damage events, combining the ground-based ICP Forests datasets. This study utilised cloud computing and Sentinel-2 satellite imagery to monitor forest health and detect anomalies. Standardised NDVI (Z NDVI) maps were produced for the period from 2017 to 2023 to identify disturbances in the forest. The research focused on seven active ICP Forests Level II and 78 Level I plots in Hungary. Z NDVI values were divided into five categories based on damage severity, and there was agreement between Level II field data and satellite imagery. In 2017, severe damage was caused by late frost and wind; however, the forest recovered by 2018. Another decline was observed in 2021 due to wind and in 2022 due to drought. Data from the ICP Forests Level I plots, which represent forest condition in Hungary, indicated that 80% of the monitored stands were damaged, with 30% suffering moderate damage and 15% experiencing severe damage. Z NDVI classifications aligned with the field data, showing widespread forest damage across the country. Full article

On 22–23 April 2025, a seismic noise survey was conducted at the Maccalube di Aragona, a mud volcano field located in Sicily (southern Italy), with the aim of characterizing the background signal associated with vent activity and the shallow subsurface structure. The experiment, named DEMETRA (DEnse MaccalubE TRomino Acquisition), was carried out within the framework of the multidisciplinary INGV-PROMUD research project, which aims to identify key indicators of mud volcano activity and potential precursors of paroxysmal events. Ambient seismic noise was recorded at 21 sites using a three-component, 24-bit digital tromograph. Measurements were conducted with a dense spatial sampling scheme covering both vent areas and peripheral zones. Preliminary data analyses included spectral estimates, computation of horizontal-to-vertical spectral ratio (HVSR) curves and evaluation of the polarization patterns. The HVSR curves do not display clear amplification peaks but rather show deamplification at specific sites. The polarization patterns exhibit spatial consistency across the vent areas. In addition, transient signals were identified in the background noise at some sites; based on their spectral and polarization characteristics, these signals are possibly associated with degassing, mud emissions, or bubbling phenomena. The dense spatial coverage of the DEMETRA experiment provides a valuable dataset for investigating subsurface properties and dynamic processes in an active mud volcano environment. Full article

The Strait of Gibraltar (SG) is a key biogeographic and ecological corridor connecting the Mediterranean Sea and the Atlantic Ocean, enabling the seasonal migrations of fin whales (Balaenoptera physalus). The objective of this study was to characterize, for the first time, the spatial and temporal exposure of the species to maritime traffic during its migration through the SG, quantifying movement patterns, individual composition, and collision risk to identify critical areas for conservation. Validated observations collected between April 2016 and October 2024, with additional records in January and March 2025, were integrated with EMODnet vessel density layers to assess monthly distributions of sightings, individuals, calves, migration patterns, and behavior. A total of 347 sightings comprising 692 individuals were recorded, revealing predominantly westward movements between June and August. Spatial overlap analyses indicated that the highest exposure occurred both near the Bay of Algeciras/Gibraltar and in the northern half of the Central SG, where cargo ship and tanker traffic coincides with dense migration routes and where injuries have been documented in the field. These findings delineate high-risk areas for fin whales throughout the SG and provide an empirical basis for spatial management measures, including speed reduction zones, adaptive route planning, and the possible designation of the area as a cetacean migration corridor. The proposed measures aim to mitigate collision risk and ensure long-term ecological connectivity between the Mediterranean and the Atlantic. Full article

This study presents a CO₂ injectivity analysis for the depleted gas field Z offshore Malaysia using nodal analysis and sensitivity analysis. Reservoir permeability was estimated from the appraisal well DST report, which recorded an absolute open flow (AOF) of 253 MMscfd, and sensitivity analyses were conducted for injection pressure, tubing diameter, reservoir pressure, permeability, and thickness. The base-case nodal analysis resulted in an optimal CO₂ injection rate of 52.3 MMscfd. Injection pressure, permeability, and thickness were linearly proportional to injection rate, whereas reservoir pressure showed an inverse relationship. The analysis of injection rate per tubing diameter indicated that 4.548-inch tubing, with 15.11 MMscfd per inch, provided the highest efficiency. A total CO₂ injection volume of 5 Tcf was distributed among five wells, and four injection period scenarios (20, 15, 10, 5 years) were designed based on flow efficiency. In the 5-year scenario, the bottomhole pressure of all wells exceeded the formation parting pressure at a reservoir pressure of approximately 1000 psia, indicating that the target injection rate of 2739 MMscfd could not be achieved. Tubing injectivity index (TII) analysis showed that higher TII values represented greater injection efficiency from a vertical flow perspective. Full article

In this study, experiments and numerical simulations were conducted to investigate the oscillation phenomena in a pressure swirl injector. The flow field was captured using high-speed photography, and the gray values were analyzed using the Matlab image processing program. The oscillation frequency was recorded using FFT transform. Additionally, the flow field of the pressure swirl injector was simulated based on the volume of fluid (VOF) interface-tracking method. Both the experimental and numerical results revealed periodic oscillations in the pressure swirl injector, with a corresponding frequency of several hundred Hertz. The oscillation frequency is closely related to the behavior of the central gas core, which has greater turbulent kinetic energy than the liquid phase. As the mass flow rate increases, the velocity of the gas core is increased. The turbulent kinetic energy of the central gas core increased, which led to an increase in the oscillation frequency. Finally, the relationship between Re and the oscillation frequency was obtained. Full article

This paper systematically analyzes the challenges of stabilizing tunnel excavations in zones with low overburden in urban environments, through an engineering-validated case study of the Kobilja Glava Tunnel. A combined approach involving the New Austrian Tunneling Method (NATM) and the pre-installation of steel pipe umbrellas was applied as the primary pre-support measure under complex geotechnical conditions. The design, drilling, grouting, and formation of the temporary support arch were thoroughly documented, along with the implementation of shotcrete, lattice girders, self-drilling anchors, and reinforcement meshes. A numerical analysis was performed using the PLAXIS 2D software package, encompassing the modeling of deformations, shear forces, axial forces, and bending moments, with precisely defined support parameters. Geodetic monitoring recorded maximum surface settlements of up to 70 mm at an overburden of less than 3 m, while deformations were reduced to 28 mm at an overburden of 20 m. The numerical model confirmed soil plasticization within a 3 m wide zone, with maximum displacements reaching 6.3 cm, consistent with field measurements. Calculated tensile strain and angular distortion were classified according to established building damage criteria, confirming minimal structural impact on adjacent buildings. The applied combination of the NATM and the pipe umbrella pre-support system proved to be an effective and reliable solution for controlling deformations and ensuring excavation stability under conditions of limited rock cover and dense urban development. The obtained results provide a verified framework and practical recommendations for future tunneling projects in similar geotechnical and urban conditions, aiming to enhance safety, stability, and cost-effectiveness. Full article

Enhancing winter wheat yield in early spring relies on optimal soil temperature (ST) conditions and robust root systems, particularly in cold and dry areas. However, the long-term combined effects of conservation tillage and plastic film mulching (PFM) on the crop root system during early spring (the period of rejuvenation and jointing) remain unstudied. This study is based on a 22-year field experiment involving two long-term conservation tillage methods: mouldboard plowing with crop residue incorporation (MC) and no-tillage with crop residue cover (NC). The main treatments were further divided by applying black (B) and white (W) plastic films to each, resulting in MC with black (MCB) and white (MCW), and NC with black (NCB) and white (NCW) films. ST was recorded at depths of 0–40 cm during the afternoon, evening, and morning, while root characteristics (RCs) were measured at the peak flowering stage at depths of 0–60 cm, and crop yield and attributes were recorded at harvest during the 2023–2024 cropping season. Compared with MC and NC, MCB and MCW increased afternoon ST by 2.5 °C and 0.94 °C, and evening ST by 1.94 °C and 1.87 °C, while NCB and NCW decreased ST. MCB and MCW also increased accumulated ST during overwintering (131–161 °C) under the tilled system. PFM on MC increased the root length and weight densities by 10–17% and 25–32%, respectively; NCB and NCW decreased RCs by 8–15.2% across the soil depth. Additionally, afternoon and evening STs at 5–20 cm positively correlated with RCs and yield attributes (r > 0.84), whereas morning ST and a 40 cm depth were negatively correlated (r < −0.77). Under tilled conditions, both MCB and MCW substantially increased grain yield (10–12%) and biomass (31–38%) compared with MC. In contrast, NCB and NCW showed no yield and biomass advantage and even reductions (16–12% and 14–3%, respectively) compared with NC. FPM improved STs, RCs, and yield under tilled conditions but not in no-till systems, highlighting the need for supplementary practices to optimize ST in no-till systems. Full article

Ductility, as a fundamental mechanical property, allows structures to undergo inelastic deformations and dissipate seismic energy while maintaining their load-carrying capacity without substantial strength degradation. Thus, the estimation of structural ductility demand has consistently constituted an essential topic of research interest in earthquake engineering. In this study, an iterative procedure for estimating the ductility demand of elastoplastic single-degree-of-freedom (SDOF) systems through dissipated energy is introduced. The proposed procedure helps the determination of ductility demand by use of only elastic response spectra. It initially estimates the hysteretic energy as a proportion of the total input energy. Then, ductility demand is estimated with the help of a developed equation by performing regression analyses based on the nonlinear time history analyses results of elastoplastic single-degree-of-freedom (SDOF) systems with a certain strength. Time history analyses were carried out by using an extensive earthquake ground motion database, which includes a total of 268 far-field records, two horizontal components from 134 recording stations located on firm soil sites. Full article

Introduction: Numerous overuse injuries affecting the lower limbs of elite athletes have been associated with biomechanical alterations in plantar loading of the foot. This study aimed to analyze the plantar pressure distribution in elite male soccer players and its relationship with various morphological and functional factors, including foot type, metatarsal and digital alignment, and on-field position. Material and Method: Dynamic foot pressure measurements were obtained from 21 soccer players who participated in the UEFA Champion League. The participants had an average age of 27 years, with an average height of 180.9 cm, weight of 76.9 kg, and BMI of 23.4. An insole system (BioFoot/IBV) with telemetry transmission was employed to record plantar loading patterns during normal gait and running. Results: During the support or contact phase, the central and medial metatarsal areas exhibited the highest peak pressure under both walking and running conditions. When walking, the right foot exerted 13–60% more pressure on the outer metatarsal and toe areas. The left foot experienced up to 13% more peak pressure in the middle metatarsal area. During running, the total pressure difference between the feet ranged from −8% to +19%. The right foot usually had more peak pressure on the heel and first toe. In players with valgus feet, the pressure in the central metatarsal area increased from 1086 kPa (walking) to 1490 kPa (running), representing a 37% increase. Conversely, in players with cavus-varus feet, the pressure in this central area increased from 877 kPa to 1804 kPa, a 105% increase. Conclusions: Foot morphology and playing position significantly influenced the plantar pressure patterns in elite soccer players. The central metatarsal region bears the highest load, particularly during running, with distinct variations across foot types and field positions. These findings highlight the need for individualized biomechanical assessments to prevent overuse injuries and optimize performance. Full article