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The Deaf are a large social group in society. Their unique way of communicating through sign language is often confined within their community due to limited understanding by individuals outside of this demographic. This is where sign language recognition (SLR) comes in to help people without hearing impairments understand the meaning of sign language. In recent years, new methods of sign language recognition have been developed and achieved good results, so it is necessary to make a summary. This review mainly focuses on the introduction of sign language recognition techniques based on algorithms especially in recent years, including the recognition models based on traditional methods and deep learning approaches, sign language datasets, challenges and future directions in SLR. To make the method structure clearer, this article explains and compares the basic principles of different methods from the perspectives of feature extraction and temporal modelling. We hope that this review will provide some reference and help for future research in sign language recognition.

Loquat is a high-value fruit tree with medicine and fruit homology. Loquat flowers with special fragrance, strong cold resistance and rich in various bioactive components, are valuable agricultural auxiliary products and have been widely used for making floral teas and beverages in recent years. In this study, we found the concentration of active components increased from the floral buds to initial flowers along with flower development, the bioactives of initial flowers were the richest in four flowering stages, and loquat flowers contained major volatile components such as alcohols, aldehydes and esters, which are the source of fragrance. When extract with hot water, the most efficient method was 80 °C for 30 min or boiling water within 2 h. For Baijiu (56% Vol), the best solid-to-liquid ratio was 3:100 (Dry flower: Baijiu) in 6–12 h. Baijiu achieved higher bioactive content than water extraction, the amygdalin concentration in Baijiu reached 0.3 mg/mL.

This paper compared the effects of air and nitrogen on the freezing characteristics, color, and cell structures of chestnut kernels at different rates of heat transfer and adopted liquid nitrogen spray quick-freezing (NF−40 °C/−60 °C/−80 °C/−100 °C) and still air freezing (AF−20 °C/−40 °C) as the freezing methods. The ratio of heat transfer coefficients in N2 groups was two times as high as those in air groups, and NF−100 °C and NF−80 °C showed better freezing characteristics, good protection for cytoskeletons, and the color was similar to those of the fresh group. Taking both Multivariate Analysis of Variance (Principal Components Analysis and Cluster Analysis) and economic factors, NF−80 °C can be used as a suitable method for chestnut kernel freezing. When the ambient freezing temperature was lower than Tg, both NF and AF treatment groups presented poor quality. The rate and medium of heat transfer jointly influenced the freezing characteristics and quality. The former had a greater effect than the latter, however.

Berries are perishable fruits with high nutritional value. Freezing is an effective way for food preservation. Freezing and thawing methods play key roles in preserving edible values and commodity values of food. This study investigated the effects of spray liquid nitrogen quick freezing (NF−20~−100 °C) and gradient thawing on the physical and functional characteristics of blueberries by using immersion and refrigerator freezing and microwave, ultrasonic, room- and low-temperature, and static-water thawing as comparisons. The results show that NF−80 °C freezing combined with −20~−5~4 °C. gradient thawing can retain more than 95% of polyphenols and other nutritional compounds (including pectin, soluble sugar, and vitamin C) in thawed blueberries compared with fresh blueberries. Besides, this method shows the best results in preserving the hardness, cell structure, and water distribution of blueberries. It is also revealed that the ultralow temperature (−100 °C) freezing does not bring a significant advantage in preserving blueberries. Rapid thawing methods such as microwave and ultrasound thawing are not suitable for blueberries, which might be due to their small size and thin skin. The results suggested that the combination of NF−80 °C freezing and −20~−5~4 °C gradient thawing is the optimal process for blueberry preservation. The outcomes of this study will serve as theoretical guidance for improving the industrial process for freezing and thawing blueberries.