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Additive manufacture (AM) has been widely and rapidly applied in fabrication of 3D porous scaffolds for tissue engineering applications. For synthetic polymers of high melting temperature, the melting-extruding technique is the most applied AM method for such fabrication of polymer porous scaffolds. This results in a big challenge to directly process the scaffolds using the polymers and thermosensitive substances simultaneously because of deactivation under high temperature. In this article, the selective laser sintering (SLS) method was proposed to make a poly(l-lactic acid) (PLLA) porous scaffold containing dexamethasone (Dex) simultaneously. Dex was encapsulated in two groups of PLLA-bioactive glass (BG) composite microspheres with an average diameter of 115-120 μm and loading amounts of 0.68 ± 0.09 and 0.84 ± 0.10 μg/mg, respectively. The drug-loading composite microspheres were then fabricated into scaffolds under a laser fluence of 0.83-2.08 J/mm

The remote video diagnosis system based on the Internet of Things is based on the Internet of Things and integrates advanced intelligent technology. To better promote a harmonious society, constructing a video surveillance system is accelerating in our country. Many enterprises and government agencies have invested much money to build video surveillance systems. The quality of video images is an important index to evaluate the video surveillance system. However, as the number of cameras continues to increase, the monitoring time continues to extend. In the face of many cameras, it is not realistic to rely on human eyes to diagnose video-solely quality. Besides, due to human eyes’ subjectivity, there will be some deviation in diagnosis through human eyes, and these factors bring new challenges to system maintenance. Therefore, relying on artificial intelligence technology and digital image processing technology, the intelligent diagnosis system of monitoring video quality is born using the computer’s efficient mathematical operation ability. Based on artificial intelligence, this paper focuses on studying video quality diagnosis technology and establishes a video quality diagnosis system for video definition detection and noise detection. This article takes the artificial intelligence algorithm in the diagnosis of video quality effect. Compared with the improved algorithm, the improved video quality diagnosis algorithm has excellent improvement and can well finish video quality inspection work. The accuracy of the improved definition evaluation function for the definition detection of surveillance video and noise detection is as high as 95.56%.

With the rapid development of information technology, a scientific theory is brought by the rapid progress of science and technology. The advancement of science and technology of the impact on every field, changing the mode of transmission of information, the advent of big data for promotion and dissemination of resources played their part, let more and more people benefit. In the context of cloud computing, big data ushered in another upsurge of development and growth. Given this, the live broadcast training platform, which focuses on enterprise staff training and network education, arises at the right moment. People favor its convenience, real-time performance, and high efficiency. However, the low-value density of big data and cloud computing’s security problem has difficulties constructing a live broadcast training platform. In this paper, the live broadcast training platform’s structure is improved by constructing three modules: the live training module based on cloud computing, the user recommendation module based on big data, and the security policy guarantee module. In addition, to ensure that the trainees can receive training anytime and anywhere, this paper uses wireless communication technology to ensure the quality and speed of all users’ live video sources.

Action recognition is the technology of understanding people’s behavior and classification from video or image sequences. This thesis uses the deep learning approach for action recognition to realize webcast supervision. This paper uses the convolutional neural network (CNN) and the Gaussian Mixture Model (GMM) to establish the webcast supervision system. At the same time, streaming-based wireless communication network technology is adopted to ensure video transmission speed and quality. Results show that the average detection speed of the system can reach 11.86 frame/s, and the average recognition accuracy is 92.16%, and the missed detection rate is lower than 5%. The design of this system can fully meet the requirements of webcast supervision.

This research was conducted to assess the structure, mechanical, barrier and optical properties of three edible composite films based on chitosan nanoparticles. Films containing cinnamon-perilla essential oil (C-PEO) Pickering nanoemulsion had denser structure and better mechanical properties. In addition, films with anthocyanidins exhibited enhanced antioxidant activity. The results showed that both Pickering nanoemulsion and anthocyanidins could improve some properties of edible composite film based on chitosan nanoparticles. Finally, preservation experiments were carried out. Analysis of storage quality indices (sensory evaluation, microbiological analyses, pH, total volatile basic nitrogen, thiobarbituric acid values, color and texture) revealed the shelf life of fillets wrapped in three kinds of composite film was extended to 6–8 days. The preservation effect of plant essential oil compound anthocyanidin edible film for fillet was the best and anthocyanidins compound chitosan nanoparticles edible film was the best in appearance of protection.

The effects of lauroyl arginate ethyl (LAE), chitosan (CTS), and CTS-containing montmorillonite and LAE coatings (CML) on the quality maintenance and shelf life of minimally processed grapes stored at 4 °C for 20 days were investigated. Compared with the control, LAE, and pure CTS coatings, the CML coatings effectively decreased grape weight loss, respiration, and decay incidence as well as microorganism counts of total aerobic bacteria, yeasts, molds, and lactic acid bacteria in grapes. The CML coatings also showed better effects on delaying the tissue softening and browning due to the decreased activities of polygalacturonase, pectin methyl esterase, and polyphenol oxidase. CML coatings did not significantly change the content of soluble solids and the titratable acidity or the pH value of grapes, compared with other samples. However, CML coatings ensured higher content of ascorbic acid and sensory quality in grapes. The results confirmed that CML coatings improve microbiological safety and preserve nutritional and sensory quality of minimally processed grapes.

This study was conducted to investigate the effects of aqueous chlorine dioxide (ClO2) combined with chitosan coating on microbial growth and quality maintenance of fresh-cut bamboo shoots during cold storage. Fresh-cut shoots respiration rate, weight loss, firmness, lignin, colour, microbial and activities of phenylalanine ammonia lyase (PAL), cinnamyl alcohol dehydrogenase (CAD), peroxidase (POD) and polyphenol oxidase (PPO) were measured. The results indicated that treatment with 28 mg L−1 ClO2 plus chitosan coating inhibited increase in respiration rate and firmness, delayed browning and lignification and reduced microorganism counts of total aerobic bacteria and yeasts and moulds compared to control treatment. The efficiency was better than that of ClO2 or chitosan treatment alone. Furthermore, combination of ClO2 and chitosan inhibited the activities of PAL, CAD, POD and PPO throughout the storage period. Our study suggests that ClO2 plus chitosan coating treatment may be a promising method of maintaining fresh-cut bamboo shoot quality and extending their postharvest life.