MIMO Channel Characteristics in Line-of-Sight Environments

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3D Stretchable Arch Ribbon Array Fabricated via Grayscale Lithography.

Microstructures with flexible and stretchable properties display tremendous potential applications including integrated systems, wearable devices and bio-sensor electronics. Hence, it is essential to develop an effective method for fabricating curvilinear and flexural microstructures. Despite significant advances in 2D stretchable inorganic structures, large scale fabrication of unique 3D microstructures at a low cost remains challenging. Here, we demonstrate that the 3D microstructures can be achieved by grayscale lithography to produce a curved photoresist (PR) template, where the PR acts as sacrificial layer to form wavelike arched structures. Using plasma-enhanced chemical vapor deposition (PECVD) process at low temperature, the curved PR topography can be transferred to the silicon dioxide layer. Subsequently, plasma etching can be used to fabricate the arched stripe arrays. The wavelike silicon dioxide arch microstructure exhibits Young modulus and fracture strength of 52 GPa and 300 MPa, respectively. The model of stress distribution inside the microstructure was also established, which compares well with the experimental results. This approach of fabricating a wavelike arch structure may become a promising route to produce a variety of stretchable sensors, actuators and circuits, thus providing unique opportunities for emerging classes of robust 3D integrated systems

Spatiotemporal variation of habitat quality and its response to fractional vegetation cover change and human disturbance in the Loess Plateau

It is of great practical significance to regional ecological conservation and restoration to explore the spatiotemporal variation characteristics of habitat quality in the ecologically fragile Loess Plateau. This study firstly explored the habitat quality in the Loess Plateau during 2000-2020 with the Integrated Valuation of Ecosystem Services and Trade-offs model. Then this study revealed the response characteristics of habitat quality to the fractional vegetation cover (FVC) change and human disturbance with the geographically weighted regression (GWR) model. Results showed habitat quality tended to improve in 51.16% of the study area, and area of high or very high habitat quality increased by 1.78%. Besides, FVC showed dominantly significant increase (62.42%) and high stability (69.66%) in the study area, and human disturbance increased remarkably in 18.11% of the study area but maintained the same level in 91.83% of the study area. Additionally, areas with positive correlation between habitat quality change and FVC and between habitat quality change and human disturbance change accounted for 52.56% and 37.38% of the study area, respectively, indicating FVC played dominant role in affecting the regional habitat quality variation. This study can provide important decision support information for the future ecological conservation of the Loess Plateau

M3^3CS: Multi-Target Masked Point Modeling with Learnable Codebook and Siamese Decoders

Masked point modeling has become a promising scheme of self-supervised pre-training for point clouds. Existing methods reconstruct either the original points or related features as the objective of pre-training. However, considering the diversity of downstream tasks, it is necessary for the model to have both low- and high-level representation modeling capabilities to capture geometric details and semantic contexts during pre-training. To this end, M$^3$CS is proposed to enable the model with the above abilities. Specifically, with masked point cloud as input, M$^3$CS introduces two decoders to predict masked representations and the original points simultaneously. While an extra decoder doubles parameters for the decoding process and may lead to overfitting, we propose siamese decoders to keep the amount of learnable parameters unchanged. Further, we propose an online codebook projecting continuous tokens into discrete ones before reconstructing masked points. In such way, we can enforce the decoder to take effect through the combinations of tokens rather than remembering each token. Comprehensive experiments show that M$^3$CS achieves superior performance at both classification and segmentation tasks, outperforming existing methods