Apple-Net: A Model Based on Improved YOLOv5 to Detect the Apple Leaf Diseases

Effective identification of apple leaf diseases can reduce pesticide spraying and improve apple fruit yield, which is significant to agriculture. However, the existing apple leaf disease detection models lack consideration of disease diversity and accuracy, which hinders the application of intelligent agriculture in the apple industry. In this paper, we explore an accurate and robust detection model for apple leaf disease called Apple-Net, improving the conventional YOLOv5 network by adding the Feature Enhancement Module (FEM) and Coordinate Attention (CA) methods. The combination of the feature pyramid and pan in YOLOv5 can obtain richer semantic information and enhance the semantic information of low-level feature maps but lacks the output of multi-scale information. Thus, the FEM was adopted to improve the output of multi-scale information, and the CA was used to improve the detection efficiency. The experimental results show that Apple-Net achieves a higher [email protected] (95.9%) and precision (93.1%) than four classic target detection models, thus proving that Apple-Net achieves more competitive results on apple leaf disease identification

Multifunctional glucose biosensors from Fe₃O₄ nanoparticles modified chitosan/graphene nanocomposites

Novel water-dispersible and biocompatible chitosan-functionalized graphene (CG) has been prepared by a one-step ball milling of carboxylic chitosan and graphite. Presence of nitrogen (from chitosan) at the surface of graphene enables the CG to be an outstanding catalyst for the electrochemical biosensors. The resulting CG shows lower ID/IG ratio in the Raman spectrum than other nitrogen-containing graphene prepared using different techniques. Magnetic Fe₃O₄ nanoparticles (MNP) are further introduced into the as-synthesized CG for multifunctional applications beyond biosensors such as magnetic resonance imaging (MRI). Carboxyl groups from CG is used to directly immobilize glucose oxidase (GOx) via covalent linkage while incorporation of MNP further facilitated enzyme loading and other unique properties. The resulting biosensor exhibits a good glucose detection response with a detection limit of 16 μM, a sensitivity of 5.658 mA/cm²/M, and a linear detection range up to 26 mM glucose. Formation of the multifunctional MNP/CG nanocomposites provides additional advantages for applications in more clinical areas such as in vivo biosensors and MRI agents.9 page(s

A case of trichilemmal cyst

A case of trichilemmal cysts is reported. A 31-year-old man presented with a 5-year history of nodule on his back with enlargement, pain and itching for 1 month. Dermatological examination showed erythema and erythematous plaques scattered on the trunk and extremities, covered with a small amount of silvery white scales. A demarcated exophytic tumor sized 2 cm×3 cm in dark red color was seen on the back, with telangiectasia on the surface. The tumor was slightly soft and tenderness (+) with poor mobility. No erosion or ulceration was observed. Histopathological examination showed a dermal cyst, which wall was composed of stratified squamous cells, and the content of cyst was keratin with focal calcification. The patient was diagnosed with trichilemmal cyst. Complete resection was given. No recurrence was observed over 4 months of follow-up

High-Performance Intraocular Biosensors from Chitosan-Functionalized Nitrogen-Containing Graphene for the Detection of Glucose

© 2019 American Chemical Society. The noninvasive and real-time detection of glucose sugar from tears is promising for the early diagnosis and treatment of chronic diseases such as diabetes. However, its realization is a big challenge. A suitable biosensor electrode that can closely fit the eye and be electrochemically sensitive is still unrealized. In this work, nitrogen-doped graphene (N-G) was used as an ophthalmic electrode in a high-performance intraocular biosensor. The use of N-G has been reported elsewhere before as it is highly electroactive and so has a particular use in biosensors. We hereby present a novel procedure for making carboxylated chitosan-functionalized nitrogen-containing graphene (GC-COOH) by using a one-step ball-milling process. This process does not use toxic chemicals, flammable gases, or a high temperature. It is thus particularly easy to perform. The fabricated nanomaterial had a high electroactivity and was easily assembled as a glucose biosensor by the immobilization of glucose oxidase. The thus constructed biosensor has a high sensitivity at 9.7 μA mM-1 cm-2, a broad linear range at 12 mM, and a good detection limit of 9.5 μM. It was able to maintain this activity after a month of storage. We also report the intraocular use of this constructed biosensor. The as-prepared GC-COOH was found to be highly biocompatible to ophthalmologic cells such as corneal epithelial and retinal pigment epithelium cells. No change in the intraocular pressure or the corneal structure was measured in a New Zealand white rabbit model. The as-assembled sensor was worn by the animals for more than 24 h without undue impact. This result confirmed the biosensor\u27s potential for intraocular application in the clinic. Its assembly into a useful sensor shown here has great potential to provide real-time monitoring of glucose levels in tear fluids of patients with high sugar levels