分类： 数字出版 >> 数字技术 提交时间： 2023-07-23
摘要： Since the year of 2022, the subculture of "crazy literature" has become increasingly popular among young people, and the discourse characteristics of its texts and the emotional motivations behind them have also begun to be concerned and discussed. Through discourse analysis, in-depth interviews and questionnaires, it can be found that in terms of discourse characteristics, "crazy literature" frequently uses rhetoric such as repetition and piling up, and constructs a clear sense of picture with logically disordered discourse; in terms of emotional motivation, "crazy literature" reflects the strong needs of youth for emotional catharsis and self-regulation; in terms of interaction mode, "crazy literature" is not an isolated emotional expression of individuals, but a carrier of youth's social desires, showing the characteristics of a "carnival" interactive ritual.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： Data from high-energy observations are usually obtained as lists of photon events. A common analysis task for such data is to identify whether diffuse emission exists, and to estimate its surface brightness, even in the presence of point sources that may be superposed. We have developed a novel non-parametric event list segmentation algorithm to divide up the field of view into distinct emission components. We use photon location data directly, without binning them into an image. We first construct a graph from the Voronoi tessellation of the observed photon locations and then grow segments using a new adaptation of seeded region growing, that we call Seeded Region Growing on Graph, after which the overall method is named SRGonG. Starting with a set of seed locations, this results in an over-segmented dataset, which SRGonG then coalesces using a greedy algorithm where adjacent segments are merged to minimize a model comparison statistic; we use the Bayesian Information Criterion. Using SRGonG we are able to identify point-like and diffuse extended sources in the data with equal facility. We validate SRGonG using simulations, demonstrating that it is capable of discerning irregularly shaped low surface-brightness emission structures as well as point-like sources with strengths comparable to that seen in typical X-ray data. We demonstrate SRGonG's use on the Chandra data of the Antennae galaxies, and show that it segments the complex structures appropriately.
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