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ABSTRACT The yield of crops has a significant impact on economic and social development. It is significant to ensure the healthy growth of crops. Leaves can represent the growth of crops. Crop health can be monitored by analyzing a sufficient number of leaf images. But advanced farming techniques make leaves less susceptible to pests and diseases. Therefore, it is difficult to collect enough leaves with pests and diseases for image analysis. To solve this problem, this research proposed a method based on few-shot learning to identify crop leaf images and judge crop health status. The main structure of the method is a siamese network. The structure of its two subnetworks is the convolution neural network with an attention module. Each subnetwork outputs a feature vector. Measuring the distance of two feature vectors in the feature space, the similarity is calculated. Then the categories of leaf pests and diseases are judged. The experiments in this research were carried out on apple and potato leaves. The accuracy of identifying their pests and diseases reached 98.03% and 97.34% respectively. The experiment proved that when the sample size is small. The method proposed can effectively identify crop leaf pests and diseases.

Abstract Background and objectives: Tramadol hydrochloride is a centrally-acting synthetic opioid analgesic binding to specific opioid receptors. It is used in the management of chronic pain and is recommended as first line drug in the treatment of postoperative or orthopedic injury induced acute pain. The present work is designed to prepare and evaluate mucoadhesive buccal film of tramadol hydrochloride as a novel form of prolonged analgesia for patients with orthopedic injuries. Methods: Buccal films of tramadol hydrochloride were prepared by solvent casting method. The prepared films were evaluated for the various evaluation parameters like thickness, surface pH, weight uniformity, content uniformity, folding endurance, swelling index, in vitro drug release study, in vitro test for mucoadhesion and in vivo studies (primary mucosal irritancy test and analgesic activity). Results: All the formulations exhibited good results for physicochemical characterizations. In in vitro drug release study the films exhibited controlled release more than 12 hours. The formulation BFT2 (containing chitosan and PVP K-90) showed no irritant effect on buccal mucosa and elicit the significant in vivo analgesic activity with 57.14% analgesia against that of standard (61.04%). It was concluded that the mucoadhesive films of tramadol hydrochloride can be effectively used to alleviate the severe pain of orthopedic injuries with prompt onset and prolonged action.