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Recent years have witnessed tremendous progress of intelligent robots brought about by mimicking human intelligence. However, current robots are still far from being able to handle multiple tasks in a dynamic environment as efficiently as humans. To cope with complexity and variability, further progress toward scalability and adaptability are essential for intelligent robots. Here, we report a brain-inspired robotic platform implemented by an unmanned bicycle that exhibits scalability of network scale, quantity and diversity to handle the changing needs of different scenarios. The platform adopts rich coding schemes and a trainable and scalable neural state machine, enabling flexible cooperation of hybrid networks. In addition, an embedded system is developed using a cross-paradigm neuromorphic chip to facilitate the implementation of diverse neural networks in spike or non-spike form. The platform achieved various real-time tasks concurrently in different real-world scenarios, providing a new pathway to enhance robots’ intelligence.

This article proposes a new recoloring method for textile fabric images based on improved fuzzy local information c-means (FLICM) clustering. In the clustering algorithm, the fuzzy factor was modified so that it can produce reliable segmentation in areas with rich details. With the obtained cluster labels and pixel-wise memberships, the color of each pixel is modeled as the linear combination of the two most dominant colors. The recoloring process was then conducted by replacing the specified dominant color with user-provided target colors. Experimental results showed that the proposed method can produce natural and faithful color appearance on both printed and yarn-dyed fabric images, and outperforms the state-of-the-art.

The coastal zone, situated at the sensitive interface between land and sea, serves as a pivotal area of human economic activities. As one of China’s economic special zones, Xiamen exemplifies the comprehensive trajectory of coastal governance in China. However, there are still research gaps in the human ecological transitions in coastal governance. This study adopts the research approach of scale politics and the local state, with the purpose of explaining the governance model of the coastal zone transformation. Sources include interviews with fishers, direct observation, participant observation, and content analysis. The study demonstrates how local governments strive to maximize the profits of scenic tourism, by (1) appropriating the international scale, absorbing international aid and technical assistance; (2) confiscating the access rights of the coastal zone; and (3) vertically integrating all relationships from local to international organizations to create new governance patterns. Xiamen’s coastal landscape not only presents the meltdown of human ecology under local state governance but also demonstrates a keen adaptation to the shifting dynamics of the international tourism market. From the theoretical perspective of the local state, this paper effectively points out the political characteristics of local government and bridges the loss of cultural ecology in the transformation of governance patterns.