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Fusarium head blight (FHB), one of the most important diseases of wheat, mainly occurs in the ear. Given that the severity of the disease cannot be accurately identified, the cost of pesticide application increases every year, and the agricultural ecological environment is also polluted. In this study, a neural network (NN) method was proposed based on the red-green-blue (RGB) image to segment wheat ear and disease spot in the field environment, and then to determine the disease grade. Firstly, a segmentation dataset of single wheat ear was constructed to provide a benchmark for the segmentation of the wheat ear. Secondly, a segmentation model of single wheat ear based on the fully convolutional network (FCN) was established to effectively realize the segmentation of the wheat ear in the field environment. An FHB segmentation algorithm was proposed based on a pulse-coupled neural network (PCNN) with K-means clustering of the improved artificial bee colony (IABC) to segment the diseased spot of wheat ear by automatic optimization of PCNN parameters. Finally, the disease grade was calculated using the ratio of the disease spot to the whole wheat ear. The experimental results show that: (1) the accuracy of the segmentation model for single wheat ear constructed in this study is 0.981. The segmentation time is less than 1 s, indicating that the model can quickly and accurately segment wheat ear in the field environment; (2) the segmentation method of the disease spot performed under each evaluation indicator is improved compared with the traditional segmentation methods, and the accuracy is 0.925 in the disease severity identification. These research results can provide important reference value for grading wheat FHB in the field environment, which also can be beneficial for real-time monitoring of other crops’ diseases under near-Earth remote sensing.

Objective: to systematically evaluate the clinical efficacy of external treatment of granulomatous mastitis (including clinical efficiency and the change of mass size). Methods: the computer was used to search CNKI, Wanfang database, VIP net, CBM, PubMed and Embase, and it was used to search and select the clinical randomized controlled trials of treating granulomatous mastitis by external treatment of traditional Chinese medicine, the retrieval time limit was from the establishment of the database to December 2020, and the key words were granulomatous mastitis, external treatment of traditional Chinese medicine. After selecting literatures, extracting datas and evaluating the risk of bias included in the study, the data included in the study were analyzed by RevMan5.3 software. Results: Seven clinical randomized controlled trials were included and 600 patients met the inclusion criteria. Seven of the trials were effective observations, and four of them were tumor size observations. There were 310 cases in the experimental group and 290 cases in the control group. All the included documents were Chinese literature. The results of the study showed that the effective rate of the experimental group (combined with the external treatment of traditional Chinese medicine) for granulomatous mastitis was 95.9%, which was significantly higher than that of the control group (without the external treatment of traditional Chinese medicine). The effective rate was 82.8% [95% CI (1.02, 1.22), Z=2.41, P=0.02

Recent research indicates that satellite diversity is a practical means of mitigating the effects of satellite fading for Mobile Satellite Systems (MSS) employing CDMA. However, the underlying assumption of such research is that satellite diversity is available all the time, which is not true in reality. We will investigate the impact of improper gateway distribution on the system capacity of MSS. We investigate the principle of distributing the gateways to ensure single and. double satellite service and present some strategies of searching for the optimal gateway distribution for single and double satellite service. To analyze the impact of gateway distributions on the system capacity of MSS, we classify the general mobile terminal environments into five states. By computing the required power margin of each state to reach the same average Bit-Error Rate (BER) and taking the occurrence probability of each state into account, the capacity of a Mobile Satellite System, expressed as the average number of mobile terminals per satellite over the area ranging from South 80° to North 80°, is analytically derived and thoroughly validated by means of computer simulations. After comparing the system capacity of a MSS with improper gateway distributions to that with the optimal gateway distribution, we show that the capacity of a MSS is decreased considerably due to improper gateway distributions. Moreover, the quantitative results indicate that a MSS in a propagation environment of light shadowing suffers more capacity loss due to improper gateway distribution than a MSS in an environment of heavy shadowing.