Search Results (143)

Medium and large-sized birds exhibit remarkable agility and maneuverability in flight, with their flapping motion encompassing degrees of freedom in flapping, twist, and swing, which enables them to adapt effectively to harsh ecological environments. This study proposes a flapping–twist coupled driving mechanism for large-scale flapping-wing aircraft by mimicking the motion patterns of birds. The mechanism generates simultaneous twist and flapping motions based on the phase difference of double cranks, allowing for the adjustment of twist amplitude through modifications in crank radius and phase difference. The objective of this work is to optimize the lift and thrust of the flapping wing to enhance its flight performance. To achieve this, we first derived the kinematic model of the mechanism and conducted motion simulations. To mitigate the effects of the flapping wing’s flexibility, a rigid flapping wing was designed and manufactured. Through wind tunnel experiments, the flapping wing system was tested. The results demonstrated that, compared to the non-twist condition, there exists an optimal twist amplitude that slightly increases the lift of the flapping wing while significantly enhancing the thrust. It is hoped that this study will provide guidance for the design of multi-degree-of-freedom flapping wing mechanisms. Full article

Dams play a vital role in securing water and electricity supplies for households and industry, and they contribute significantly to flood protection. Regular monitoring of dam deformations holds fundamental socio-economic and ecological importance. Traditionally, this has relied on time-consuming in situ techniques that offer either high spatial or temporal resolution. Persistent Scatterer Interferometry (PSI) addresses these limitations, enabling high-resolution monitoring in both domains. Sensors such as TerraSAR-X (TSX) and Sentinel-1 (S-1) have proven effective for deformation analysis with millimeter accuracy. Combining TSX and S-1 datasets enhances monitoring capabilities by leveraging the high spatial resolution of TSX with the broad coverage of S-1. This improves monitoring by increasing PS point density, reducing revisit intervals, and facilitating the detection of environmental deformation drivers. This study aims to investigate two objectives: first, we evaluate the benefits of a spatially and temporally densified PS time series derived from TSX and S-1 data for detecting radial deformations in individual dam segments. To support this, we developed the TSX2StaMPS toolbox, integrated into the updated snap2stamps workflow for generating single-master interferogram stacks using TSX data. Second, we identify deformation drivers using water level and temperature as exogenous variables. The five-year study period (2017–2022) was conducted on a gravity dam in North Rhine-Westphalia, Germany, which was divided into logically connected segments. The results were compared to in situ data obtained from pendulum measurements. Linear models demonstrated a fair agreement between the combined time series and the pendulum data ($R^2$ = 0.5; MAE = 2.3 mm). Temperature was identified as the primary long-term driver of periodic deformations of the gravity dam. Following the filling of the reservoir, the variance in the PS data increased from 0.9 mm to 3.9 mm in RMSE, suggesting that water level changes are more responsible for short-term variations in the SAR signal. Upon full impoundment, the mean deformation amplitude decreased by approximately 1.7 mm toward the downstream side of the dam, which was attributed to the higher water pressure. The last five meters of water level rise resulted in higher feature importance due to interaction effects with temperature. The study concludes that integrating multiple PS datasets for dam monitoring is beneficial particularly for dams where few PS points can be identified using one sensor or where pendulum systems are not installed. Identifying the drivers of deformation is feasible and can be incorporated into existing monitoring frameworks. Full article

Vegetation is a fundamental component of terrestrial ecosystems. Understanding how vegetation changes and what drives these evolutions is crucial for developing a high-quality ecological environment and addressing global climate change. Extensive evidence has shown that China has undergone substantial vegetation changes, characterized primarily by greening. To quantify vegetation dynamics in China and assess the contributions of various drivers, we explored the spatiotemporal variations in the kernel Normalized Difference Vegetation Index (kNDVI) from 2001 to 2020, and quantitatively separated the influences of climate and human factors. The kNDVI time series were generated from the MCD19A1 v061 dataset based on the Google Earth Engine (GEE) platform. We employed the Theil-Sen trend analysis, the Mann-Kendall test, and the Hurst index to analyze the historical patterns and future trajectories of kNDVI. Residual analysis was then applied to determine the relative contributions of climate change and human activities to vegetation dynamics across China. The results show that from 2001 to 2020, vegetation in China showed a fluctuating but predominantly increasing trend, with a significant annual kNDVI growth rate of 0.002. The significant greening pattern was observed in over 48% of vegetated areas, exhibiting a clear spatial gradient with lower increases in the northwest and higher amplitudes in the southeast. Moreover, more than 60% of vegetation areas are projected to experience a sustained increase in the future. Residual analysis reveals that climate change contributed 21.89% to vegetation changes, while human activities accounted for 78.11%, being the dominant drivers of vegetation variation. This finding is further supported by partial correlation analysis between kNDVI and temperature, precipitation, and the human footprint. Vegetation dynamics were found to respond more strongly to human influences than to climate drivers, underscoring the leading role of human activities. Further analysis of tree cover fraction and cropping intensity data indicates that the greening in forests and croplands is primarily attributable to large-scale afforestation efforts and improved agricultural management. Full article

The circadian clock orchestrates behavioral and molecular processes such as eclosion. Understanding eclosion timing may offer insights into circadian mechanisms underlying migratory timing. Here, we characterize the diel and circadian patterns of eclosion and core clock gene expression in the fall armyworm (FAW), Spodoptera frugiperda, a globally distributed migratory moth. Using a custom-designed eclosion monitoring system under 14 h light: 10 h dark (L14: D10) and constant darkness (DD) conditions, we observed robust diel eclosion rhythms peaking shortly after lights-off under L14: D10, which became delayed and damped over three consecutive days in DD. Males showed a tendency toward more dispersed emergence patterns and exhibited statistically distinguishable eclosion distributions from females under both conditions. Expression of five canonical clock genes (cyc, clk, tim, per, cry2) displayed significant 24 h rhythmicity, with generally higher mesors in males. However, sex-specific differences in amplitude and phase were detected only for clk and cyc under L14: D10, not in DD. These findings suggest that sex-specific differences in circadian regulation are limited. Nonetheless, subtle variations in clock gene output and emergence timing in the FAW population established in China may contribute to sex-specific ecological strategies in the novel migratory arena. Full article

Argentina anserina (Rosaceae), a perennial herb, forms enlarged tuberous roots (commonly referred to as “ginseng fruit”) exclusively in the Qinghai–Tibet Plateau, making it a unique medicinal and edible plant resource in this region. The upper reaches of the Dadu River and Minjiang River are one of its primary production areas in China. This study employs an ensemble model to simulate the potential distribution of A. anserina in this region, predicting the impacts of future climate change on its distribution, ecological niche, and centroid migration patterns. Additionally, a cultivation productivity evaluation model integrating ecological suitability and nutritional components was developed to delineate potential cultivation areas. Results indicate that high-suitability habitats span 0.37 × 10⁴ km² (7.39% of the total suitable area), exhibiting a patchy and fragmented distribution in Aba County, Rangtang County, Jiuzhi County, and Banma County. Core cultivation areas cover 3.78 × 10⁴ km², distributed across Aba County, Rangtang County, Jiuzhi County, Seda County, Banma County, Hongyuan County, and Markam City. Under future climate scenarios, the suitable distribution area of A. anserina will gradually decline with rising temperatures, migrating to higher-latitude northern regions, accompanied by increased niche migration. By the 2090s under the SSP5-8.5 scenario, the centroid demonstrates the largest migration amplitude, with high-suitability habitats showing a “collapsing” polarization pattern and near-complete niche separation from the previous period, indicating significant changes. Collectively, these results provide a theoretical basis for the sustainable utilization of A. anserina in the upper Dadu River and Minjiang River basin. Full article

The daily operation of cascade hydropower stations induces periodic water level fluctuations (WLFs) that propagate as gravity waves, significantly affecting the hydrodynamics of reservoirs. Previous studies have mainly focused on the effects of individual stations, with little attention paid to the combined impacts of upstream and downstream operations. Taking the Wudongde Reservoir on the Jinsha River as a case study, we used a one-dimensional hydrodynamic model and cross-correlation analysis to simulate flow fluctuation patterns under joint daily operations. The results show that fluctuations from upstream stations attenuate rapidly in the reservoir, with greater attenuation during the dry season. Under joint operations, wave energy decayed exponentially near the reservoir tail and linearly in the main reservoir area, leading to a further reduction in the WLF amplitudes. The interactions between upstream- and downstream-propagating waves enhance energy dissipation. The wave type transitioned from kinematic to dynamic as the water depth increased. During the wet and dry seasons, the average wave velocities were approximately six and nine times higher, respectively, than those under natural conditions. Joint operations expand the range of potential slope instability but reduce the WLF rate compared to natural flows. These findings provide a scientific reference for optimising the daily operations of cascade hydropower stations and mitigating their ecological impacts. Full article

This paper focuses on the stability issues of geological and engineering structures and conducts research from two perspectives: the mechanism of slope landslides under micro-seismic action and the cyclic failure behavior of concrete materials. In terms of slope stability, through the combination of model tests and theories, the cumulative effect of circulating micro-seismic waves on the internal damage of slopes was revealed. This research finds that the coupling of micro-vibration stress and static stress significantly intensifies the stress concentration on the slope, promotes the development of potential sliding surfaces and the extension of joints, and provides a scientific basis for the prediction of landslide disasters. This helps protect mountain ecosystems and reduce soil erosion and vegetation destruction. The number of cyclic loads has a power function attenuation relationship with the compressive strength of concrete. After 1200 cycles, the strength drops to 20.5 MPa (loss rate 48.8%), and the number of cracks increases from 2.7 per mm³ to 34.7 per mm³ (an increase of 11.8 times). Damage evolution is divided into three stages: linear growth, accelerated expansion, and critical failure. The influence of load amplitude on the number of cracks shows a threshold effect. A high amplitude (>0.5 g) significantly stimulates the propagation of intergranular cracks in the mortar matrix, and the proportion of intergranular cracks increases from 12% to 65%. Grey correlation analysis shows that the number of cycles dominates the strength attenuation (correlation degree 0.87), and the load amplitude regulates the crack initiation efficiency more significantly (correlation degree 0.91). These research results can optimize the design of concrete structures, enhance the durability of the project, and indirectly reduce the resource consumption and environmental burden caused by structural damage. Both studies are supported by numerical simulation and experimental verification, providing theoretical support for disaster prevention and control and sustainable engineering practices and contributing to ecological environment risk management and the development of green building materials. Full article

Particleboard is an important forest product that can be reprocessed using wood processing by-products. This approach has the potential to achieve significant conservation of forest resources and contribute to the protection of forest ecology. Most current detection models require a significant number of tagged samples for training. However, with the advancement of industrial technology, the prevalence of surface defects in particleboard is decreasing, making the acquisition of sample data difficult and significantly limiting the effectiveness of model training. Deep reinforcement learning-based detection methods have been shown to exhibit strong generalization ability and sample utilization efficiency when the number of samples is limited. This paper focuses on the potential application of deep reinforcement learning in particleboard defect detection and proposes a novel detection method, PPOBoardNet, for the identification of five typical defects: dust spot, glue spot, scratch, sand leak and indentation. The proposed method is based on the proximal policy optimization (PPO) algorithm of the Actor-Critic framework, and defect detection is achieved by performing a series of scaling and translation operations on the mask. The method integrates the variable action space and the composite reward function and achieves the balanced optimization of different types of defect detection performance by adjusting the scaling and translation amplitude of the detection region. In addition, this paper proposes a state characterization strategy of multi-scale feature fusion, which integrates global features, local features and historical action sequences of the defect image and provides reliable guidance for action selection. On the particleboard defect dataset with limited images, PPOBoardNet achieves a mean average precision (mAP) of 79.0%, representing a 5.3% performance improvement over the YOLO series of optimal detection models. This result provides a novel technical approach to the challenge of defect detection with limited samples in the particleboard domain, with significant practical application value. Full article

The slurry collected from the waste water resulting from ceramic tile processing contains significant amounts of quartz, kaolinite, and mullite, along with traces of iron hydroxides as observed using XRD analysis coupled with mineralogical optical microscopy (MOM). Such an admixture would be ideal for the development of ecologic building materials. Microstructural conditioning enhances the binding properties of kaolinite. Therefore, the influence of the vibration compaction of the moistened slurry at 30% humidity on the compressive strength was assessed. The compressive strength of the unvibrated sample is about 0.8 MPa with failure promoted by the microstructural unevenness. Several vibration amplitudes were tested from 20 to 40 mm. The optimal vibration mode was obtained at an amplitude of 25 mm for 10 min, ensuring a compressive strength of 2.37 MPa with a smooth and uniform failure surface involved within the binding layer as observed using SEM microscopy. The samples prepared under optimal conditions were thermally consolidated at 700, 800, and 900 °C below the mullitization temperature to ensure a low carbon footprint. XRD results reveal kaolinite dehydration in all fired samples, inducing its densification, which increases with increasing heating temperature. SEM coupled with EDS elemental investigations reveal that the dehydrated kaolinite better embeds quartz and mullite particles, ensuring a compact microstructure. The binding strength increases with the firing temperature. The mullite particles within the samples fired at 900 °C induce the partial mullitization of the dehydrated kaolinite matrix, increasing their homogeneity. The compression strength of the fired samples is temperature dependent: 4.44 MPa at 700 °C; 5.88 MPa at 800 °C, and 16.87 MPa at 900 °C. SEM fractography shows that failure occurs due to the dehydrated kaolinite matrix cracks and the quartz particles. The failure is rather plastic at low temperatures and becomes brittle at 900 °C. Reducing the firing temperature and treatment time reduces the carbon footprint of the consolidated ceramic parts. Samples fired at 700 °C exhibit a compressive strength comparable to low quality bricks, those fired at 800 °C exhibit a strength comparable to regular bricks, and those fired at 900 °C exhibit a superior strength comparable to high-quality bricks. Full article

Dams are crucial for ensuring water and electricity supply, while also providing significant flood protection. Regular monitoring of dam deformations is of vital socio-economic and ecological significance. In Germany, dams must be constructed and operated according to generally accepted rules of engineering. The safety concept for dams based on these rules relies on structural safety, professional operation and maintenance, safety monitoring, and precautionary measures. Rather time-consuming in situ techniques have been employed for these measurements, which permit monitoring deformations with either high spatial or temporal resolution, but not both. As a means of measuring large-scale deformations in the millimeter range, the Differential Interferometric Synthetic Aperture Radar (DInSAR) technique of Persistent Scatterer Interferometry (PSI) is already being applied in various fields. However, when considering the operational monitoring of dams using PSI, specific characteristics need to be considered. For example, the geographical location of the dam in space, as well as its shape, size, and land cover. All these factors can affect the visibility of the structure for the use with PSI and, in certain cases, limit the applicability of SAR data. The visibility of dams for PSI monitoring is often limited, particularly in cases where observation is typically not feasible due to factors such as geographical and structural characteristics. While corner reflectors can improve visibility, their large size often makes them unsuitable for dam infrastructure and may raise concerns with heritage protection for listed dams. Addressing these challenges, electronic corner reflectors (ECRs) offer an effective alternative due to their small and compact size. In this study, we analyzed the strategic placement of ECRs on dam structures. We developed a new CR Index, which identifies areas where PSI alone is insufficient due to unfavorable geometric or land use conditions. This index categorizes visibility potential into three classes, presented in a ‘traffic light’ map, and is instrumental in selecting optimal installation sites. We furthermore investigated the signal stability of ECRs over an extended observation period, considering the Amplitude Dispersion Index (ADI). It showed values between 0.1 and 0.4 for many dam structures, which is comparable to normal corner reflectors (CRs), confirming the reliability of these signals for PSI analysis. This work underscores the feasibility of using ECRs to enhance monitoring capabilities at dam infrastructure. Full article

Coal mining disrupts soil structure and causes water loss, thereby affecting the ecological environment of mining areas. Rapid, accurate, and non-destructive detection of surface soil moisture is crucial for advancing ecological restoration in these regions. This study focuses on the mined and unmined areas of the Yushuquan coal mine, located on the southern slope of the Tianshan Mountains in Xinjiang, China. The soil volumetric water content (SVWC) was measured using time-domain reflectometry (TDR), while the shallow subsurface soil was investigated using ground-penetrating radar (GPR). Various features were extracted from GPR signals in both the time- and frequency-domains, and their relationships with SVWC were analyzed. Multiple features were selected and optimized to determine the optimal feature combination for building a multi-feature backpropagation neural network model for soil volumetric water content prediction (Muti-BP-SVWC). The performance of this model was compared with two single-feature-based methods for SVWC prediction: the average envelope amplitude (AEA) method and the frequency shift method. The application results of the Muti-BP-SVWC model in different regions demonstrated significant improvements in accuracy and stability compared to the AEA method and the frequency shift method. In the mined area validation set, the model achieved an determination coefficient (R²) of 0.77 and the root mean square error (RMSE) of 0.0091 cm³/cm³, while in the unmined area validation set, the R² of 0.84 and an RMSE of 0.0059 cm³/cm³. These results indicate that incorporating multiple features into the BP neural network can better capture the complex relationship between GPR signals and SVWC. This approach effectively inverts the shallow subsurface soil moisture in mining areas and provides valuable guidance for ecological restoration in these regions. Full article

The article presented the results of the assessment of the current state of Rhaponticum altaicum populations in the Karaganda and Akmola regions (Central and Northern Kazakhstan). The research provided the phytocenotic characteristics of habitats, biological features, and ontogenetic structure of populations, as well as data on the morphological variability of the species. The floristic composition of plant communities with Rh. altaicum was analyzed for the first time. In the plant communities with Rh. altaicum, 67 species from 38 genera and 23 families were identified. Most species were herbaceous perennials (92.5%) or hemicryptophytes (68.7%). Among the ecological groups, mesophytes (32.8%) dominated, and other groups were represented by transitional species: mesoxerophytes, xeromesophytes, mesogyrophytes, and hygromesophytes (49.2%). Therefore, in nature, Rh. altaicum occupied an intermediate place between meadow-bog and meadow communities. The species preferred moist meadows on slightly and moderately saline soils. In the ontogeny of Rh. altaicum, eight age-related states were identified, from seedlings to senile plants. The analysis of morphological indices allowed estimating that Rh. altaicum stem height was the most important; so, under unfavorable growing conditions, the stem height decreased. In the majority of populations, the upper leaf width was a highly variable trait, and the length and width of the lower leaf had low or moderate morphological variability. The highest positive correlation (significant at p = 0.05) was between plant height and lower leaf length, suggesting that taller plants had longer lower leaf blades. The studied populations were mainly dominated by virgin and medium-age generative plants. Sub-senile and senile plants were not detected, which is due to the difficulty of diagnosis as well as to the increasing anthropogenic load and narrow ecological amplitude of Rh. altaicum. Our study provided new insights into Rh. altaicum biology and ecology, thereby contributing to biodiversity conservation at a regional level. Full article

Silver lime is a thermophilic, calciphile species that thrives in xero-mesophilic forest communities. The westernmost edge of its natural distribution is Zrinska Gora Mountain in central Croatia, where it is found in almost all types of forest vegetation, albeit with varying frequencies. Its ecological optimum is in specific ravines and grooves, where it forms the mesophilic, relict broad-leaved ravine forest community Polysticho setiferi-Tilietum tomentosae. This research was conducted on two levels. Firstly, the communities of Zrinska Gora were analyzed as the westernmost edge of the natural distribution. Secondly, the ecology of the Tilia tomentosa communities in the western part of its distribution (Croatia, Bosnia and Herzegovina, Hungary, and Serbia) was observed. Analysis of Ellenberg-type indicator values for 74 communities from the western Balkans revealed a slight trend of decreasing thermophilicity and increasing acidophilicity toward the western edge of the distribution area. Silver lime peripheral populations on Zrinska Gora develop under unique ecological conditions. The soil reaction of all communities falls below the lower limit of the optimal range for its development, and the relict association experiences lower temperature values compared to the other communities. All in all, the results of this study provide insights into the adaptability of silver lime to climate change. Full article

The time–frequency characteristics of dolphin whistle signals under diverse ecological conditions and during environmental changes are key research topics that focus on the adaptive and response mechanisms of dolphins to the marine environment. To enhance the quality and utilization of passive acoustic monitoring (PAM) recorded dolphin whistles, the challenges faced by current wavelet thresholding methods in achieving precise threshold denoising under low signal-to-noise ratio (SNR) are confronted. This paper presents a thresholding denoising method based on stationary wavelet transform (SWT), utilizing suppression impulsive and autocorrelation function (SI-ACF) to select precise thresholds. This method introduces a denoising metric $\rho$, based on the correlation of whistle signals, which facilitates precise threshold estimation under low SNR without requiring prior information. Additionally, it exploits the high amplitude and broadband characteristics of impulsive noise, and utilizes the multi-resolution information of the wavelet domain to remove impulsive noise through a multi-level sliding window approach. The SI-ACF method was validated using both simulated and real whistle datasets. Simulated signals were employed to evaluate the method’s denoising performance under three types of typical underwater noise. Real whistles were used to confirm its applicability in real scenarios. The test results show the SI-ACF method effectively eliminates noise, improves whistle signal spectrogram visualization, and enhances the accuracy of automated whistle detection, highlighting its potential for whistle signal preprocessing under low SNR. Full article

Permeable dams are an important means for river management and ecology protection. Reasonable dam spacing will help regulate sediment transport and reduce sediment load in lakes. Flume experiments were carried out to investigate the effects of hydrological sediment conditions and dam spacing on sediment retention performance and permeability of the cascade permeable dams. The experimental results show that the permeability coefficient of the 1# dam decreased by about 30–40% with a large rate during the initial experiment stage. The decrease amplitude in the permeability coefficient and rising rate of the water level in front of the 1# dam for a large dam spacing (D/L) are positively correlated with the flow rate. At D/L = 5, the water level difference of 1# dam at the end of the experiment was significantly higher than that of other spacing. The sediment mass retained by 1# dam accounts for about 41–65% of the total sediment mass retained, which is about twice that of 2# dam, and plays a major role in cascade permeable dams. A mathematical model for predicting the spatial-temporal sediment concentration inside 1# dam is proposed based on the seepage theory of porous media. The research results are of great guiding significance for the design of the dam parameters. Full article