Edge Detection in UAV Remote Sensing Images Using the Method Integrating Zernike Moments with Clustering Algorithms

Due to the unmanned aerial vehicle remote sensing images (UAVRSI) within rich texture details of ground objects and obvious phenomenon, the same objects with different spectra, it is difficult to effectively acquire the edge information using traditional edge detection operator. To solve this problem, an edge detection method of UAVRSI by combining Zernike moments with clustering algorithms is proposed in this study. To begin with, two typical clustering algorithms, namely, fuzzy c-means (FCM) and K-means algorithms, are used to cluster the original remote sensing images so as to form homogeneous regions in ground objects. Then, Zernike moments are applied to carry out edge detection on the remote sensing images clustered. Finally, visual comparison and sensitivity methods are adopted to evaluate the accuracy of the edge information detected. Afterwards, two groups of experimental data are selected to verify the proposed method. Results show that the proposed method effectively improves the accuracy of edge information extracted from remote sensing images

Analysis of Walking-Edge Effect in Train Station Evacuation Scenarios: A Sustainable Transportation Perspective

Due to the highly developed rail transit over the past decades, the phenomena of complex individual self-organized behaviors and mass crowd dynamics have become a great concern in the train station. In order to understand passengers&rsquo walking-edge effect and analyze the relationship between the layout and sustainable service abilities of the train station, a heuristics-based social force model is proposed to elaborate the crowd dynamics. Several evacuation scenarios are implemented to describe the walking-edge effect in a train station with the evacuation efficiency, pedestrian flow, and crowd density map. The results show that decentralizing crowd flow can significantly increase the evacuation efficiency in different scenarios. When the exits are far away from the central axis of the railway station, the walking-edge effect has little influence on the evacuation efficiency. Obstacles can guide the movement of passengers by channelizing pedestrian flows. In addition, a wider side exit of the funnel-shaped corridors can promote walking-edge effect and decrease the pressure among a congested crowd. Besides providing a modified social force model with considering walking-edge effect, several suggestions are put forward for managers and architects of the train station in designing sustainable layouts. Document type: Articl

Vibration Damping of Carbon Nanotube Assembly Materials

Vibration reduction is of great importance in various engineering applications, and a material that exhibits good vibration damping along with high strength and modulus has become more and more vital. Owing to the superior mechanical property of carbon nanotube (CNT), new types of vibration damping material can be developed. This paper presents recent advancements, including our progresses, in the development of high-damping macroscopic CNT assembly materials, such as forests, gels, films, and fibers. In these assemblies, structural deformation of CNTs, zipping and unzipping at CNT connection nodes, strengthening and welding of the nodes, and sliding between CNTs or CNT bundles are playing important roles in determining the viscoelasticity, and elasticity as well. Towards the damping enhancement, strategies for micro-structure and interface design are also discussed

Electrohydrodynamic Printing of a Dielectric Elastomer Actuator and Its Application in Tunable Lenses

Optical lenses driven by dielectric elastomer (DE) actuators with tunable focal lengths are presented here. They are inspired by the architecture of the crystalline lens and the ciliary muscle of the human eye and have prompted a growing interest. The most commonly used DEs in tunable lenses have often required highly transparent films and also the need to encapsulate clear liquid silicone to act as the lens. There is a restriction on the properties of the tunable lens imposed by materials limitations. Here, the fabrication of a fully 3D printed tunable lens with an inhomogeneous structure is described. It exhibited a 29% change in focal length from 33.6 mm to 26.1 mm under a dynamic driving voltage signal control. Furthermore, it displayed excellent stability when the focal length was tuned from far to near (30.1 mm to 25.3 mm) for 200 cycles. The tunable lens obtained mimics the working principle of the human eye in auto adjusting the focal length and has evident potential applications in imaging, information storage, beam steering and bifocal technology

A flexible dual-mode pressure sensor with ultra-high sensitivity based on BTO@MWCNTs core-shell nanofibers

Wearable flexible sensors have developed rapidly in recent years because of their improved capacity to detect human motion in wide-ranging situations. In order to meet the requirements of flexibility and low detection limits, a new pressure sensor was fabricated based on electrospun barium titanate/multi-wall carbon nanotubes (BTO@MWCNTs) core-shell nanofibers coated with styrene-ethylene-butene-styrene block copolymer (SEBS). The sensor material (BTO@MWCNTs/SEBS) had a SEBS to BTO/MWCNTs mass ratio of 20:1 and exhibited an excellent piezoelectricity over a wide range of workable pressures from 1 to 50 kPa, higher output current of 56.37 nA and a superior piezoresistivity over a broad working range of 20 to 110 kPa in compression. The sensor also exhibited good durability and repeatability under different pressures and under long-term cyclic loading. These properties make the composite ideal for applications requiring monitoring subtle pressure changes (exhalation, pulse rate) and finger movements. The pressure sensor developed based on BTO@MWCNTs core-shell nanofibers has demonstrated great potential to be assembled into intelligent wearable devices

Impact of a pyridazine derivative on tripartite synapse ultrastructure in hippocampus: a three-dimensional analysis

IntroductionWe previously discovered a pyridazine derivative compound series that can improve cognitive functions in mouse models of Alzheimer’s disease. One of the advanced compounds from this series, LDN/OSU-0215111-M3, was selected as the preclinical development candidate. This compound activates local protein translation at the perisynaptic astrocytic process (PAP) and enhances synaptic plasticity sequentially. While biochemical evidence supports the hypothesis that the compound enhances the structural plasticity of the tripartite synapse, its direct structural impact has not been investigated.MethodsVolume electron microscopy was used to study the hippocampal tripartite synapse three-dimensional structure in 3-month-old wild-type FVB/NJ mice after LDN/OSU-0215111-M3 treatment.ResultsLDN/OSU-0215111-M3 increased the size of tertiary apical dendrites, the volume of mushroom spines, the proportion of mushroom spines containing spine apparatus, and alterations in the spine distribution across the surface area of tertiary dendrites. Compound also increased the number of the PAP interacting with the mushroom spines as well as the size of the PAP in contact with the spines. Furthermore, proteomic analysis of the isolated synaptic terminals indicated an increase in dendritic and synaptic proteins as well as suggested a possible involvement of the phospholipase D signaling pathway. To further validate that LDN/OSU-0215111-M3 altered synaptic function, electrophysiological studies showed increased long-term potentiation following compound treatment.DiscussionThis study provides direct evidence that pyridazine derivatives enhance the structural and functional plasticity of the tripartite synapse