Transformers for Remote Sensing: A Systematic Review and Analysis.

Research on transformers in remote sensing (RS), which started to increase after 2021, is facing the problem of a relative lack of review. To understand the trends of transformers in RS, we undertook a quantitative analysis of the major research on transformers over the past two years by dividing the application of transformers into eight domains: land use/land cover (LULC) classification, segmentation, fusion, change detection, object detection, object recognition, registration, and others. Quantitative results show that transformers achieve a higher accuracy in LULC classification and fusion, with more stable performance in segmentation and object detection. Combining the analysis results on LULC classification and segmentation, we have found that transformers need more parameters than convolutional neural networks (CNNs). Additionally, further research is also needed regarding inference speed to improve transformers' performance. It was determined that the most common application scenes for transformers in our database are urban, farmland, and water bodies. We also found that transformers are employed in the natural sciences such as agriculture and environmental protection rather than the humanities or economics. Finally, this work summarizes the analysis results of transformers in remote sensing obtained during the research process and provides a perspective on future directions of development.

Application of Identification and Evaluation Techniques for Edible Mushrooms: A Review.

Edible mushrooms are healthy food with high nutritional value, which is popular with consumers. With the increase of the problem of mushrooms being confused with the real and pollution in the market, people pay more and more attention to food safety. More than 167 articles of edible mushroom published in the past 20 years were reviewed in this paper. The analysis tools and data analysis methods of identification and quality evaluation of edible mushroom species, origin, mineral elements were reviewed. Five techniques for identification and evaluation of edible mushrooms were introduced and summarized. The macroscopic, microscopic and molecular identification techniques can be used to identify species. Chromatography, spectroscopy technology combined with chemometrics can be used for qualitative and quantitative study of mushroom and evaluation of mushroom quality. In addition, multiple supervised pattern-recognition techniques have good classification ability. Deep learning is more and more widely used in edible mushroom, which shows its advantages in image recognition and prediction. These techniques and analytical methods can provide strong support and guarantee for the identification and evaluation of mushroom, which is of great significance to the development and utilization of edible mushroom.

More studies are necessary to establish the effectiveness of Jinhuang powder in the treatment of diabetic foot.

Diabetes mellitus is a common global public health problem that can cause serious illness and premature death. Diabetic foot ulcer, one of the complications of diabetes, is a major cause of morbidity and mortality and is associated with many other devastating complications. Previous study found that a group of traditional Chinese medicine (TCM) can be used for treating diabetic foot ulcers. More and more attention is being paid to the use of Chinese medicine to heal diabetic feet. Under the guidance of relevant theories of traditional Chinese medicine, more studies are needed to reveal the key active components and related signal pathways of TCM in the treatment of diabetic foot ulcer. One clinical study explored the treatment of diabetic foot with infection combined moist exposed burn ointment with Jinhuang powder. However, large-scale multi-center, double blind, randomized, placebo-controlled clinical trials and animal studies are necessary to establish the effectiveness of Jinhuang powder in the treatment of diabetic foot.