Tumor microenvironment (TME) is the survival environment for tumor cells to proliferate and metastasize in deep tissue. TME contains tumor cells, immune cells, stromal cells and a variety of active molecules including reactive oxygen species (ROS). Inside the TME, ROS regulate the oxidation–reduction (redox) homeostasis and promote oxidative stress. Due to the rapid proliferation ability and specific metabolic patterns of the TME, ROS pervade virtually all complex physiological processes and play irreplaceable roles in protein modification, signal transduction, metabolism, and energy production in various tumors. Therefore, measurements of the dynamically, multicomponent simultaneous changes of ROS in the TME are of great significance to reveal the detailed proliferation and metastasis mechanisms of the tumor. Near-infrared (NIR) and two-photon (TP) fluorescence imaging techniques possess real-time, dynamic, highly sensitive, and highly signal-to-noise ratios with deep tissue penetration abilities. With the rationally designed probes, the NIR and TP fluorescence imaging techniques have been widely used to reveal the mechanisms of how ROS regulates and constructs complex signals and metabolic networks in TME. Therefore, we summarize the design principles and performances of NIR and TP fluorescence imaging of ROS in the TME in the last four years, as well as discuss the advantages and potentials of these works. This Review can provide guidance and prospects for future research work on TME and facilitate the development of antitumor drugs.

To continue to protect and inherit the cultural landscape heritage of traditional villages, starting from the perspective of artificial intelligence (AI), literature review methods are used, and related theories are collected. Then, Wuyuan County in Jiangxi Province in the traditional villages is taken as the research object. By analyzing the tourism income of this place from 2016 to 2020, the overall income of this county is relatively good. In fact, due to the weak protection of traditional villages in Wuyuan County, the lack of supervision awareness, the implementation of the “immigrant and relocation” policy, and the backward thinking of residents, the cultural landscape of traditional villages has collapsed and destroyed. Up to now, there are 113 ancient ancestral temples, 28 ancient mansion houses, 36 ancient private houses, 187 ancient bridges, and only 12 ancient villages. Finally, AI technology is applied to the cultural landscape of traditional villages. Through image restoration technology, traditional villages can be restored to a certain extent. Intelligent positioning and radio frequency (RF) technology can also realize real-time monitoring of traditional villages from the perspective of weather and service life to achieve the purpose of protecting cultural landscape heritage. Therefore, AI technology is applied in the protection and inheritance of traditional village cultural landscape heritage, which has great reference significance for the management of various historical and cultural heritage.

To inherit the essential characteristics of regionality, diversity, and artistry of the landscape “Grotto-Heavens and Blissful Lands,” this study takes Mount Jingfu, a model of that in the Lingnan Region, as the research object. It is based on the Cultural and Regional Disposition Theory under landscape architecture esthetics and summarizes the esthetic features of Mount Jingfu from three dimensions: (i) regional and technical characteristics of adaptation to local conditions, elaborately utilizing and arranging the space, and drawing on local materials; (ii) social milieu of seeking inner pleasure and integrating different cultures, worshipping numeral immortals and benefiting the folks, and embracing simplicity and bold innovation; (iii) artistic and human qualities of clarity and quiescence, exquisiteness and elegance, and morality and righteousness. The study is conducive to promoting the regional conservation and living inheritance of Lianzhou’s culture of blissful lands and presenting the esthetic characteristics of renowned mountain landscape resources.

With the advancement and development of the Internet, Flash has penetrated into all aspects of people's lives. As a popular multimedia, Flash has the advantages of strong artistic expressions, simple manufacture, flexible interaction and small storage, so Flash is widely used on the Internet. Currently, the shortages of researches about extracting content features of Flash seriously impose restrictions on the retrieval and utilization of Flash. Therefore, this paper proposes a novel method called FLCFE which is used for extracting content structure features from Flash. The method can effectively extract the content features of Flash, such as metadata information and component elements. On the basis of optimizing the efficiency of FLCFE, we build an experimental prototype of FLCFE through C++. Several simulation experiments based on three parameters, the Precision Ratio, the Recall Ratio and the Time Consumption, have been carried out respectively. Results show that FLCFE not only has good performances of the Recall Ratio and the Precision Ratio, but also has stable performance of time efficiency.