Cyclic load is widely adopted in laboratory to simulate the effect of train load on ballast bed. The effectiveness of such load equivalence is usually testified by having similar results of key concerns of ballast bed, such as deformation or stiffness, while the consistency of particle scale characteristics under two loading patterns is rarely examined, which is insufficient to well-understand and use the load simplification. In this study, a previous laboratory model test of ballast bed under cyclic load is rebuilt using 3D discrete element method (DEM), which is validated by dynamic responses monitored by high-resolution sensors. Then, train load having the same magnitude and amplitude as the cyclic load is applied in the numerical model to obtain the statistical characteristics of inter-particle contact force and particle movements in ballast bed. The results show that particle scale responses under two loading patterns could have quite deviation, even when macro-scale responses of ballast bed under two loading patterns are very close. This inconsistency indicates that the application scale of the DEM model should not exceed the validation scale. Moreover, it is important to examine multiscale responses to validate the effectiveness of load simplification.
Background: Spinal cord injury (SCI) is a severe neurological disorder for which there is currently no effective treatment. Electroacupuncture (EA) is a means of combining traditional acupuncture with modern electrotherapy, which has been widely used and verified to have neuroprotective effects. The aim of this study was to evaluate the effects of EA treatment on the repair of SCI and to investigate the possible mechanisms. Methods: Rats were randomly divided into sham, sham+EA, SCI and SCI+EA four groups after SCI model was established. Rat motor function was assessed by the Basso, Beattie and Bresnahan locomotor rating scale, inclined plane test and footprint analysis. Histological alterations were examined with hematoxylin-eosin and Nissl staining. Oxidative stress was evaluated by measuring reactive oxygen species (ROS), glutathione (GSH), total antioxidant capacity (T-AOC), 3-nitrotyrosine (3-NT), as well as 4-hydroxynonenal (4-HNE) levels. The expression of p66Shc and endoplasmic reticulum stress (ERS) were detected to explore the involved mechanisms.Results: EA treatment significantly improved motor functional recovery, reduced spinal cord lesion cavity and neuronal chromatolysis after SCI. Meanwhile, EA treatment alleviated oxidative stress, as indicated by suppression of ROS production, increase in GSH and T-AOC levels and reduction of 3-NT and 4-HNE expression. Further, EA stimulation markedly eliminated the aberrant increase of p66Shc due to SCI in rats. More notably, EA treatment also attenuated ERS via down-regulation of glucose-regulated protein 78, activating transcription factor 4, C/EBP homologous protein, X-box binding protein 1 and activating transcription factor 6 expression in rat spinal cord tissues after SCI. Conclusions: These findings suggest that EA is a potential strategy for treatment of SCI, and the mechanism might be, at least in part, associated with mitigation of p66Shc-mediated oxidative stress and ERS in rats.
Setting false targets is one of the important means of battlefield camouflage. The survivability of protected targets largely depends on the effect of photoelectric deception and jamming of false targets. The comprehensive use of robust image features plays a key role in correctly evaluating the photoelectric deception jamming efficiency of false targets and quickly identifying true and false targets. The existing efficiency evaluation models lack systematic research on the robustness of various image features in different environments. There are common problems of single target background and incomplete consideration of environmental factors, which lead to the instability of the extracted target image features, and then affect the evaluation results.Given the above problems, two kinds of environmental conditions are set: the change of observation distance and the change of atmospheric attenuation intensity. The experimental environment is simulated by an equivalent simulation method. After filtering the target background interference and extracting the target subject image and features, the similarity measurement method is used to calculate the similarity between true and false target subject images. By comparing the changes of gray distribution, contour, and texture feature similarity value, the robustness ranking and change reasons of features under different environmental conditions are summarized. At the same time, experiments are designed to verify the robustness of gray distribution features. The results show that the gray distribution feature has strong robustness, and the combination of gray distribution feature on the battlefield can effectively help officers and soldiers identify true and false targets in a complex environment.
Given the lack of a standardized evaluation system for the infrared jamming effectiveness of false targets, this paper first uses a co-saliency detection model to extract the main parts of the true and false targets. Then the perceptual similarity algorithm is improved by combining the operational requirements of false targets in the infrared band. Finally, a background-independent evaluation model for infrared jamming effectiveness of false targets is constructed. The experimental results show that the model can quantitatively reflect the infrared jamming effectiveness of a single false target and distinguish the infrared jamming effectiveness of different types of false targets. In addition, the model has stronger robustness than traditional evaluation models.
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