Battery management system (BMS) refers to a critical electronic control unit in the power battery system of electric vehicles. It is capable of detecting and estimating battery status online, especially estimating state of charge (SOC) and state of health (SOH) accurately. Safe driving and battery life optimization are of high significance. As indicated from recent literature reports, most relevant studies on battery health estimation are offline estimation, and several problems emerged (e.g., long time-consuming, considerable calculation and unable to estimate online). Given this, the present study proposes an online estimation method of lithium-ion health based on particle swarm support vector machine algorithm. By exploiting the data of National Aeronautics and Space Administration (NASA) battery samples, this study explores the changing law of battery state of charge under different battery health. In addition, particle swarm algorithm is adopted to optimize the kernel function of the support vector machine for the joint estimation of battery SOC and SOH. As indicated from the tests (e.g., Dynamic Stress Test), it exhibits good adaptability and feasibility. This study also provides a certain reference for the application of BMS system in electric vehicle battery online detection and state estimation.

In the biologic production of succinic acid or cadaverine, an alkali or acid is used for neutralization during the production process and for dissociation during purification.

Nattokinase from fermentation has recently gained more attention due to its beneficial effects on cardiovascular system. However, the instability of free nattokinase limits its application. The aim of the study was to develop a spray‐drying microencapsulation process to obtain the nattokinase powder with high activity, high quality, and strong storage stability. Hence, the microencapsulation process of nattokinase from fermentation by spray drying was optimized. Experiments of single‐factor and response surface methodology were used to assess the comprehensive scores and nattokinase activities. According to single‐factor and response surface methodology results, optimum parameters of microencapsulation process of the nattokinase power by spray drying were 30% of mass ratio of wall materials, 139°C of air inlet temperature, 8 L/h of feed rate, and 80°C of outlet temperature. The final optimized result encompassed a comprehensive score of 96, nattokinase activity of 1,340 IU/ml, and moisture content of 4.1 ± 0.1%. In addition, the microencapsulated nattokinase power showed strong storage stability in the conditions of different temperatures and pH. After 30 days of storage, the nattokinase powder was still white or light yellow, with a special smell, no peculiar smell and paste taste, and no impurity. These results build the basis of further industrialization of the nattokinase powder from fermentation broth by spray drying.

Cadaverine carbamate, capturing the self-released carbon dioxide from the decarboxylation of l-lysine, is the green and sustainable separation of bio-based cadaverine.

Pigs’ backfat quality has an important impact on the quality of pork and pork products and has a strong relationship with nutrition and sensory characteristics. This study aimed to identify the related candidate genes of backfat quality and to preliminary clarify the molecular regulatory mechanism underlying pig backfat quality phenotypes. Expression assessments of long non-coding RNA (lncRNA) and mRNA profiling in backfat from high-quality (firm and white) and low-quality (soft and yellow) Beijing Black pigs were performed by RNA sequencing. Significantly different expressions were observed in 610 protein-coding genes and 290 lncRNAs between the two groups. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway annotation showed that some candidate differentially expressed genes that participate in lipid-related pathways and pigmentation terms may play a role in backfat quality in pigs. The cis-target and trans-target genes were predicted to explore the regulatory function of lncRNAs, and integrative analyses of different expression lncRNAs targets and different expression genes were performed. The results showed the regulatory networks of lncRNA-mRNA related to backfat quality, and our study obtained strong candidate genes for backfat quality: ELOVL5, SCD, DGAT2, SLC24A5, and TYRP1, which were involved in fat metabolism, adipogenesis regulation, and pigmentation. To our knowledge, this study is the first to demonstrate the molecular genetic mechanisms of backfat quality in pigs, and these findings improve the current understanding of backfat quality mechanisms and provide a foundation for further studies.