Search Results (16)

Railway catenary layout drawings (RCLDs) have the characteristics of upper and lower symmetry, a large drawing size, a small size, high similarity among target symbols, and an uneven distribution of symbol categories. These factors make the symbol detection task more complex and challenging. To address the aforementioned challenges, this paper proposes three enhancements to YOLOv8n to improve symbol detection performance and integrates an improved denoising diffusion probabilistic model (IDDPM) to mitigate the imbalance in symbol category distribution. First, the multi-scale dilated attention (MSDA) is introduced in the Neck part to enhance the model’s perception of the global context in complex RCLD scenes, so that it can more effectively capture the symbol information distributed in different scales and backgrounds. Secondly, the receptive field attention convolution (RFAConv) is used in the detection head to replace the standard convolution, to improve the ability to focus on the target symbols in RCLDs and effectively alleviate the occlusion interference between symbols. Finally, the dynamic upsampler (DySample) is used to enhance the clarity and positioning accuracy of the edge area of small target symbols in RCLDs and enhance the detection of small targets. The above design made targeted optimizations to resolve the problems of symbol and background interference, character overlap, and symbol category imbalances in complex scenes in RCLDs, effectively improving the overall detection performance of the model. Compared with the baseline YOLOv8n model, the improved YOLOv8n achieves increases of 2.9% in F1, 1.9% in mAP@0.5, and 1.7% in mAP@0.5:0.95. With the introduction of synthetic data, the recognition of minority-class symbols is further enhanced, leading to additional gains of 4%, 3.8%, and 14% in F1, mAP@0.5, and mAP@0.5:0.95, respectively. These results demonstrate the effectiveness and superiority of the proposed method in improving detection performance. Full article

Olives are a crucial woody oil crop, the harvesting of which predominantly relies on manual labor, which is characterized by high costs, low efficiency, and challenges in ensuring optimal harvesting timing. The development of an automated ripeness-detection system with high recognition accuracy is of paramount importance for advancing automated olive-harvesting technologies. Traditional detection methods are constrained by susceptibility to environmental interference, limited robustness, and inadequate generalization capabilities. Concurrently, existing deep learning-based detection models face issues such as insufficient feature extraction for small targets and difficulties in deployment due to their need for large numbers of parameters. To address these limitations, this study proposes a lightweight algorithm for detection and grading of olive ripeness based on an Improved YOLOv11n framework. The proposed approach employs YOLOv11n as the baseline model, replaces its backbone network with EfficientNet-B0, and integrates the Large-Scale Kernel Attention (LSKA) mechanism and the Bidirectional Feature Pyramid Network (BiFPN). Experimental validation demonstrated that the enhanced model achieved detection accuracy comparable to that of the original model, attaining a mean average precision (mAP) of 0.918. Furthermore, the model size was reduced to 3.7 MB, a 39.3% reduction, while the computational complexity (GFLOPs) was decreased by 2.4 and the inference time per image was reduced by 0.2 ms. The proposed model exhibits significant advantages in terms of lightweight design and improved detection efficiency, demonstrating substantial potential for practical deployment. This study provides a valuable reference for the development of automated olive-harvesting technologies. Full article

Variable-coefficient viscous dampers (VVDs) have a variable annular gap, allowing them to dynamically adjust the damping coefficient at different displacement stages and provide higher damping forces during large displacement phases. This study evaluates the seismic performance of a steel frame equipped with VVDs. A shaking table test was conducted on a two-story, single-span steel frame with the VVDs to assess its seismic response, and the results were compared with those of the same frame equipped with conventional viscous dampers (VD). The experimental results demonstrated that the VVDs significantly reduced the structural dynamic response at various levels of earthquake intensity, consistently outperforming the VDs in terms of the seismic reduction effectiveness. Subsequently, a constitutive model for the VVD element was developed using the open-source finite element software OpenSees3.3.0. The accuracy of the developed element was validated by comparing the finite-element analysis results with mechanical performance tests of the VVD. Based on the developed VVD element, a numerical model of test structure was established in OpenSees for time–history analyses. The results showed good agreement between the numerical simulations and shaking table test data. Finally, a parametric study was conducted on the effects of the ratio $r$ of the second-order damping coefficient to the first-order damping coefficient and the velocity index α of the VVD on the seismic response of the numerical model of the tested structure. The results indicated that the seismic reduction rate of the tested structure increased with $r$, with a maximum improvement of 24%, while it decreased with increasing α, with a maximum reduction of 27%. Full article

The implementation of scientific cultivation practices on soda saline–alkali land plays a pivotal role in safeguarding food security and promoting sustainable agro-economic development at the regional scale. However, there exists a critical knowledge gap regarding the optimization of tillage strategies for rain-fed maize (Zea mays L.) cultivation across heterogeneous saline–alkali soil matrices. This study selected meadow alkaline soil, saline meadow soil, and mild saline–alkali soil under the typical micro-landscape morphological characteristics of soda saline–alkali soil in the Songnen Plain as experimental plots. Under three tillage methods, namely no tillage (NT), rotary tillage + no tillage (RT), and subsoiling + rotary tillage + no tillage (SRT), the effects of the tillage methods on the soil physical properties at the seedling stage, root development at the V6 stage, and yield at the R6 stage during the process of cultivating maize in different types of soils were analyzed. The research results showed that compared with NT and RT, the SRT treatment better improved the physical properties, such as penetration resistance and the bulk density in micro-spaces (0–40 cm), of different soil types. The SRT treatment had a positive impact on the root development of maize seedlings in saline meadow soil and meadow alkaline soil. In terms of yield, compared with the NT treatment, the SRT treatment in meadow alkaline soil and saline meadow soil had a positive effect on the plant height, root dry weight, 1000–grain weight, and grain yield of maize. The increases in maize grain yield were 27.94% and 13.24%, respectively. Compared with NT, the differences in the effects of the SRT and RT treatments on maize yield in mild saline-alkali soil were the smallest, being 6.98% and 4.77%, respectively. The relevant results provide guidance on tillage methods and a theoretical basis for improving the properties of different types of soda saline–alkali soils and increasing maize yield. Full article

With the rapid development of unmanned aerial vehicles (UAVs), UAV-based communications have shown promising application prospects in beyond-fifth-generation (B5G) and sixth-generation (6G) communication. Air-to-ground (A2G) channel characteristics are significant for UAV-based wireless communications. In this paper, a multi-UAV channel measurement system is developed, which can realize cooperative, accurate, and real-time channel measurements. Measurement campaigns are performed in the campus scenario at the 3.6 GHz frequency band. Based on the measurement data, cross-correlation properties of some typical large-scale channel parameters are extracted and analyzed, including the power delay profile (PDP), path loss (PL), and shadow fading (SF). The analysis results reveal that the cross-correlation of PDP remains larger than 0.6 during the whole measurement, and the decorrelation distance is 14.765 m. The cross-correlation of SF is relatively low, and the decorrelation distance is found to be 4.628 m. These results can provide valuable references for optimizing multi-link UAV communications and node placements. Full article

In this research, a finite element model is established to investigate effective seismic control schemes for a self-anchored suspension bridge (SASB) with three towers. Nonlinear dynamic analyses are conducted to evaluate the seismic performance of SASB with different layout schemes of viscous dampers and buffers, which were installed in longitudinal direction and transversal direction, respectively. The responses of the SASB designed with 10 seismic control schemes are compared to ascertain suitable seismic schemes for SASBs. The results show that the number and location of lateral buffers have an important impact on the dynamic characterization of the SASB, especially for the first lateral mode and lateral fundamental frequency. To effectively increase the seismic performance of SASBs with three towers, mounting buffers between the side towers and the main girder of SASBs is an appropriate scheme. The viscous dampers can effectively decrease the dynamic reaction of the towers and longitudinal deformation of the girder under earthquake excitations. The plan involves the installation of dampers between the main concrete stiffening girder and the side towers as the optimal longitudinal seismic scheme for the SASB. The study offers important insights into the seismic design of SASBs with three towers. Full article

To build a DEM model of Cyperus esculentus seed particles, the shape and size of the Cyperus esculentus seed particles were measured and analyzed. The results showed that the dispersity in size had a normal distribution. Additionally, a certain functional relationship between the primary dimension and secondary dimensions was determined. The width of the seed was the primary dimension, and the other secondary dimensions (length and thickness) were calculated based on their relationships with the primary dimension. On this basis, an approach for modeling Cyperus esculentus seed particles based on the multi-sphere (MS) method was proposed. The discrete element analysis models of three varieties of Cyperus esculentus seeds were established with different numbers of filing spheres. Moreover, to obtain more accurate simulation parameters, first, a range of values of the simulation parameters was obtained by the experimental method. Second, the Plackett–Burman (PB) test and the path of steepest ascent method were both adopted to correct and calibrate the simulation parameters, which were difficult to obtain through experiments, and simulation of the direct shear test was used for calibration. All of the methods guaranteed that the selected parameters were reasonable. The test results showed that the static friction coefficient of seed–seed had a significant effect on the simulation results. Finally, piling tests and the bulk density test were used for modeling verification. By comparing the simulated results and experimental results in the piling tests and bulk density test, when the number of filing spheres increased, the simulated results were close to those obtained experimentally. Therefore, the feasibility and validity of the modeling method for Cyperus esculentus seed particles that we proposed and the simulation parameters that were obtained were verified. Full article

The forest community structure and dynamic structure provide basic data for in-depth study of the community maintenance mechanisms and succession processes of urban forest ecosystems. Moreover, the study on the dynamics of suburban forest communities can provide a reference for the succession process of forest communities under severe human disturbance. In this context, this study analyzes the species composition and community structure of a 6 ha subtropical secondary evergreen broad-leaved forest plot in Wuchaoshan National Forest Park, Hangzhou, Eastern China. There are 36,757 existing woody plants (with DBH ≥ 1 cm), belonging to 94 species (45 evergreen species, and 48 deciduous species) in 63 genera of 34 families, with a plant density of 6126 plants/ha. The overall size–class distribution shows an obvious inverted “J” shape. Species with the top-five important values in the sample are Schima superba, Camellia fraternal, Symplocos anomala, Cyclobalanopsis glauca, Eurya rubiginosa, accounting for 57.3% of all individuals within the sample. In addition, different species have different habitat preferences and different distribution areas. The Wuchaoshan forest is in the middle and late stages of the succession. Different interference histories in the community succession process are demonstrated through studies of secondary evergreen broad-leaved forests. Long-term community monitoring contributes to indicating the direction and potential of the secondary forest succession. Full article

As the number of civil aerial vehicles increase explosively, spectrum scarcity and security become an increasingly challenge in both the airspace and terrestrial space. To address this difficulty, this paper presents an unmanned aerial vehicle-assisted (UAV-assisted) spectrum mapping system and a spectrum data reconstruction algorithm driven by spectrum data and channel model are proposed. The reconstruction algorithm, which includes a model-driven spectrum data inference method and a spectrum data completion method with uniformity decision mechanism, can reconstruct limited and incomplete spectrum data to a three-dimensional (3D) spectrum map. As a result, spectrum scarcity and security can be achieved. Spectrum mapping is a symmetry-based digital twin technology. By employing an uniformity decision mechanism, the proposed completion method can effectively interpolate spatial data even when the collected data are unevenly distributed. The effectiveness of the proposed mapping scheme is evaluated by comparing its results with the ray-tracing simulated data of the campus scenario. Simulation results show that the proposed reconstruction algorithm outperforms the classical inverse distance weighted (IDW) interpolation method and the tensor completion method by about 12.5% and 92.3%, respectively, in terms of reconstruction accuracy when the collected spectrum data are regularly missing, unevenly distributed and limited. Full article

Highways provide key social and economic functions but generate a wide range of environmental consequences that are poorly quantified and understood. Here, we developed a before–during–after control-impact remote sensing (BDACI-RS) approach to quantify the spatial and temporal changes of environmental impacts during and after the construction of the Wujing Highway in China using three buffer zones (0–100 m, 100–500 m, and 500–1000 m). Results showed that land cover composition experienced large changes in the 0–100 m and 100–500 m buffers while that in the 500–1000 m buffer was relatively stable. Vegetation and moisture conditions, indicated by the normalized difference vegetation index (NDVI) and the normalized difference moisture index (NDMI), respectively, demonstrated obvious degradation–recovery trends in the 0–100 m and 100–500 m buffers, while land surface temperature (LST) experienced a progressive increase. The maximal relative changes as annual means of NDVI, NDMI, and LST were about −40%, −60%, and 12%, respectively, in the 0–100m buffer. Although the mean values of NDVI, NDMI, and LST in the 500–1000 m buffer remained relatively stable during the study period, their spatial variabilities increased significantly after highway construction. An integrated environment quality index (EQI) showed that the environmental impact of the highway manifested the most in its close proximity and faded away with distance. Our results showed that the effect distance of the highway was at least 1000 m, demonstrated from the spatial changes of the indicators (both mean and spatial variability). The approach proposed in this study can be readily applied to other regions to quantify the spatial and temporal changes of disturbances of highway systems and subsequent recovery. Full article

Gross primary production (GPP) determines the amounts of carbon and energy that enter terrestrial ecosystems. However, the tremendous uncertainty of the GPP still hinders the reliability of GPP estimates and therefore understanding of the global carbon cycle. In this study, using observations from global eddy covariance (EC) flux towers, we appraised the performance of 24 widely used GPP models and the quality of major spatial data layers that drive the models. Results show that global GPP products generated by the 24 models varied greatly in means (from 92.7 to 178.9 Pg C yr⁻¹) and trends (from −0.25 to 0.84 Pg C yr⁻¹). Model structure differences (i.e., light use efficiency models, machine learning models, and process-based biophysical models) are an important aspect contributing to the large uncertainty. In addition, various biases in currently available spatial datasets have found (e.g., only 57% of the observed variation in photosynthetically active radiation at the flux tower locations was explained by the spatial dataset), which not only affect GPP simulation but more importantly hinder the simulation and understanding of the earth system. Moving forward, research into the efficacy of model structures and precision of input data may be more important for global GPP estimation. Full article

Considering the three-dimensional (3D) trajectory, 3D antenna array, and 3D beamforming of unmanned aerial vehicle (UAV), a novel non-stationary millimeter wave (mmWave) geometry-based stochastic model for UAV to vehicle communication channels is proposed. Based on the analysis results of measured and ray tracing simulation data of UAV mmWave communication links, the proposed parametric channel model is constructed by a line-of-sight path, a ground specular path, and two strongest single-bounce paths. Meanwhile, a new parameter computation method is also developed, which is divided into the deterministic (or geometry-based) part and the random (or empirical) part. The simulated power delay profile and power angle profile demonstrate that the statistical properties of proposed channel model are time-variant with respect to the scattering scenarios, positions and beam direction. Moreover, the simulation results of autocorrelation functions fit well with the theoretical ones as well as the measured ones. Full article

In this paper, a discrete non-stationary multiple-input multiple-output (MIMO) channel model suitable for the fixed-point realization on the field-programmable gate array (FPGA) hardware platform is proposed. On this basis, we develop a flexible hardware architecture with configurable channel parameters and implement it on a non-stationary MIMO channel emulator in a single FPGA chip. In addition, an improved non-stationary channel emulation method is employed to guarantee accurate channel fading and phase, and the schemes of other key modules are also illustrated and implemented in a single FPGA chip. Hardware tests demonstrate that the output statistical properties of proposed channel emulator, i.e., the probability density function (PDF), cross-correlation function (CCF), Doppler power spectrum density (DPSD), and the power delay profile (PDP) agree well with the corresponding theoretical ones. Full article

This article explores the integration of Marxism into the Gospel narratives of the Christian Bible in Zhu Weizhi’s Jesus the Proletarian (1950). It argues that Zhu in this Chinese Life of Jesus refashioned a Gospel according to Marxism, with a proletarian Jesus at its center, by creatively appropriating a wealth of global sources regarding historical Jesus and primitive Christianity. Zhu’s rewriting of Jesus can be appreciated as a precursor to the later Latin American liberation Christology. Full article

Vimentin (VIM) is a surface receptor for enterovirus-A71, mediating the initial binding and subsequent increase in EV-A71 infectivity. The caspid protein VP1 variation, A289T, is reportedly closely associated with less severe central nervous system (CNS) infections in humans. However, it is unclear whether VIM is associated with a reduction in CNS infections of EV-A71 in the presence of A289T. We investigated whether VIM served as a receptor for EV-A71 in the presence of an A298T substitution in VP1. EV-A71-289A and EV-A71-289T were used to infect human rhabdomyosarcoma cells, control human brain microvascular endothelial cells (HBMECs), and VIM-knockout (KO) HBMECs and inoculated BALB/c mice, SV129 mice, and VIM-KO SV129 mice. Furthermore, we cloned VP1-289A-Flag and VP1-289T-Flag proteins for co-immunoprecipitation analysis. Analysis of viral function revealed that the capacity of viral attachment, replication, and protein synthesis and secretion decreased in HBMECs during an EV-A71-289A infection, the infectivity being higher than that of EV-A71-289T upon VIM-KO. Histopathological and immunohistochemical analyses of brain tissue revealed that cerebral cortical damage was more extensive in EV-A71-289A than in EV-A71-289T infections in control SV129 mice; however, no significant difference was observed upon VIM-KO. Co-immunoprecipitation analysis revealed an interaction between VP1 and VIM, which was attenuated in VP1 harboring A289T; however, this attenuation was reversed by VIM (1-58) peptide. The A289T variation of VP1 specifically decreased the virulence of EV-A71 in HBMECs, and the attenuated interaction between VP1 harboring the A289T variation and VIM essentially decreased the CNS infectivity of EV-A71 in vitro and vivo. Full article