The novel working principle enables spiking cameras to capture high-speed moving objects. However, the applications of spiking cameras can be affected by many factors, such as brightness intensity, detectable distance, and the maximum speed of moving targets. Improper settings such as weak ambient brightness and too short object-camera distance, will lead to failure in the application of such cameras. To address the issue, this paper proposes a modeling algorithm that studies the detection capability of spiking cameras. The algorithm deduces the maximum detectable speed of spiking cameras corresponding to different scenario settings (e.g., brightness intensity, camera lens, and object-camera distance) based on the basic technical parameters of cameras (e.g., pixel size, spatial and temporal resolution). Thereby, the proper camera settings for various applications can be determined. Extensive experiments verify the effectiveness of the modeling algorithm. To our best knowledge, it is the first work to investigate the detection capability of spiking cameras.
Archaea are important participants in biogeochemical cycles of metal(loid)-polluted ecosystems, whereas archaeal structure and function in response to metal(loid) contamination remain poorly understood. Here, the effects of multiple metal(loid) pollution on the structure and function of archaeal communities were investigated in three zones within an abandoned sewage reservoir. We found that the high-contamination zone (Zone I) had higher archaeal diversity but a lower habitat niche breadth, relative to the mid-contamination zone (Zone II) and low-contamination zone (Zone III). Particularly, metal-resistant species represented by potential methanogens were markedly enriched in Zone I (cumulative relative abundance: 32.24%) compared to Zone II (1.93%) and Zone III (0.10%), and closer inter-taxon connections and higher network complexity (based on node number, edge number, and degree) were also observed compared to other zones. Meanwhile, the higher abundances of potential metal-resistant and methanogenic functions in Zone I (0.24% and 9.24%, respectively) than in Zone II (0.08% and 7.52%) and Zone III (0.01% and 1.03%) suggested archaeal functional adaptation to complex metal (loid) contamination. More importantly, six bioavailable metal(loid)s (titanium, tin, nickel, chromium, cobalt, and zinc) were the main contributors to archaeal community variations, and metal(loid) pollution reinforced the role of deterministic processes, particularly homogeneous selection, in the archaeal community assembly.