A Multi-Sensor System for Silkworm Cocoon Gender Classification via Image Processing and Support Vector Machine

Silk fibroin-based biomaterials for cartilage/osteochondral repair

Osteoarthritis (OA) is a common joint disease with a high disability rate. In addition, OA not only causes great physiological and psychological harm to patients, but also puts great pressure on the social healthcare system. Pathologically, the disintegration of cartilage and the lesions of subchondral bone are related to OA. Currently, tissue engineering, which is expected to overcome the defects of existing treatment methods, had a lot of research in the field of cartilage/osteochondral repair. Silk fibroin (SF), as a natural macromolecular material with good biocompatibility, unique mechanical properties, excellent processability and degradability, holds great potential in the field of tissue engineering. Nowadays, SF had been prepared into various materials to adapt to the demands of cartilage/osteochondral repair. SF-based biomaterials can also be functionally modified to enhance repair performance further. In this review, the preparation methods, types, structures, mechanical properties, and functional modifications of SF-based biomaterials used for cartilage/osteochondral repair are summarized and discussed. We hope that this review will provide a reference for the design and development of SF-based biomaterials in cartilage/osteochondral repair field.

Bibliometric Analysis of Trends in Mulberry and Silkworm Research on the Production of Silk and Its By-Products

Simple Summary

Over the past two decades scientific research on sericulture, the agricultural activity of silk production, generated a great number of outputs in the form of articles reported and classified by one of the most well-known and used database dealing with scientific literature. This occurrence demonstrates an increasing interest in this sector especially starting from 2000s; results presented in relevant papers showed their applicability even in fields apparently not related to silk production as commonly meant, like medicine, cosmetics, and engineering. To understand how sericulture has been transcending its usual boundaries, which are its current “hotspots”, and links with other fields of study, the authors propose a text-mining based analysis of the outputs of scientific research on sericulture and silk; the final goal is to establish “quantitative” indicators for researchers, entrepreneurs, and scholars.

Abstract

Traditionally, sericulture is meant as the agricultural activity of silk production, from mulberry (Morus sp.pl.) cultivation to silkworm (Bombyx mori L.) rearing. The aim of the present work is to analyze the trends and outputs of scientific research on sericulture-related topics during the last two decades, from 2000 to 2020. In this work the authors propose a text-mining analysis of the titles, abstracts and keywords of scientific articles focused on sericulture and available in the SCOPUS database considering the above-mentioned period of time; from this article collection, the 100 most recurrent terms were extracted and studied in detail. The number of publications per year in sericulture-related topics increased from 87 in 2000 to 363 in 2020 (+317%). The 100 most recurrent terms were then aggregated in clusters. The analysis shows how in the last period scientific research, besides the traditional themes of sericulture, also focused on alternative products obtainable from the sericultural practice, as fruits of mulberry trees (increment of +134% of the occurrences in the last five years) and chemical compounds as antioxidants (+233% of occurrences), phenolics (+330% of occurrences) and flavonoids (+274% of occurrences). From these considerations, the authors can state how sericulture is an active and multidisciplinary research field.

Deep learning enhanced terahertz imaging of silkworm eggs development

Terahertz (THz) technology lays the foundation for next-generation high-speed wireless communication, nondestructive testing, food safety inspecting, and medical applications. When THz technology is integrated by artificial intelligence (AI), it is confidently expected that THz technology could be accelerated from the laboratory research stage to practical industrial applications. Employing THz video imaging, we can gain more insights into the internal morphology of silkworm egg. Deep learning algorithm combined with THz silkworm egg images, rapid recognition of the silkworm egg development stages is successfully demonstrated, with a recognition accuracy of ∼98.5%. Through the fusion of optical imaging and THz imaging, we further improve the AI recognition accuracy of silkworm egg development stages to ∼99.2%. The proposed THz imaging technology not only features the intrinsic THz imaging advantages, but also possesses AI merits of low time consuming and high recognition accuracy, which can be extended to other application scenarios.