Effect of Molecular Structure Modification and Nano-Doping on Charge Transportation of Polyimide Films for Winding Insulation

Polyimide (PI) is widely employed as winding insulation in high voltage devices, such as extra-high voltage electric reactor and inverter-fed motor. The injection and accumulation of charges on the surface of PI films will lead to electrical field distortion and reduced lifespan of winding insulation, especially for the operation environment of high temperature and high voltage. This chapter focuses on effects of surface molecular modification and nanoparticles on dynamic characteristics of surface charge and space charge of pure PI films, including three sections. The effect of molecular structure on the surface charge dynamics of PI films was studied firstly. The chapter investigated that how molecular structure affects surface charge of polyimide nanocomposite films. Furthermore, the effect of surface molecular modification on space charge characteristics of multilayer PI films was researched. The results illustrate that surface molecular modification and nanoparticles can comprehensively suppress space charge accumulation and improve dielectric property

Local Community Detection Algorithm Based on Minimal Cluster

In order to discover the structure of local community more effectively, this paper puts forward a new local community detection algorithm based on minimal cluster. Most of the local community detection algorithms begin from one node. The agglomeration ability of a single node must be less than multiple nodes, so the beginning of the community extension of the algorithm in this paper is no longer from the initial node only but from a node cluster containing this initial node and nodes in the cluster are relatively densely connected with each other. The algorithm mainly includes two phases. First it detects the minimal cluster and then finds the local community extended from the minimal cluster. Experimental results show that the quality of the local community detected by our algorithm is much better than other algorithms no matter in real networks or in simulated networks

Time Course Transcriptomic Study Reveals the Gene Regulation During Liver Development and the Correlation With Abdominal Fat Weight in Chicken

Background: The liver is the central metabolic organ of animals. In chicken, knowledge on the relationship between gene expression in the liver and fat deposition during development is still limited. A time-course transcriptomic study from the embryonic (day 12) to the egg-producing period (day 180 after hatch) was performed to profile slow-growing meat type chicken liver gene expression and to investigate its correlation with abdominal fat deposition.Results: The transcriptome profiles showed a separation of the different developmental stages. In total, 13,096 genes were ubiquitously expressed at all the tested developmental stages. The analysis of differentially expressed genes between adjacent developmental stages showed that biosynthesis of unsaturated fatty acids pathway was enriched from day 21 to day 140 after hatch. The correlation between liver gene expression and the trait abdominal fat weight (AFW) was analyzed by weighted gene co-expression network analysis. The genes MFGE8, HHLA1, CKAP2, and ACSBG2 were identified as hub genes in AFW positively correlated modules, which suggested important roles of these genes in the lipid metabolism in chicken liver.Conclusion: Our results provided a resource of developmental transcriptome profiles in chicken liver and suggested that the gene ACSBG2 among other detected genes can be used as a candidate gene for selecting low AFW chickens

Quantitative Detection and Uncertainty Analysis of Low-level Presence of Genetically Modified Ingredient in Soybean

In this study, the low-level presence of genetically modified (GM) soybean event GTS-40-3-2 was quantitatively detected and the measurement uncertainty was estimated. Within 95% confidence interval, the quantitative method developed using real-time polymerase chain reaction (PCR) and digital PCR could stably detect 0.01% GTS-40-3-2 content with acceptable cost and uncomplicated operation, while the digital PCR method could quantify 0.1% GTS-40-3-2 content accurately, and the quantitative error did not exceed 50% even at GTS-40-3-2 content as low as 0.05%. The sources of uncertainty in quantitative digital PCR analysis were analyzed, and the calculation formula for uncertainty was derived from calculation models in analytical chemistry. Furthermore, GTS-40-3-2 was used for laboratory verification. The expanded uncertainty in quantitative analysis of 0.1% and 0.05% GTS-40-3-2 contents was calculated as 23.56% and 107.29% (k = 2), respectively

Comparison of Proteome Differences between Whole Milk and Skim Milk Based on High-throughput Quantitative Proteomics

Protein is an important nutrient in bovine milk, however, it is not clear about the effect of defatting on the protein content of bovine milk. In this paper, quantitative proteomics labeled with TMT (tandem mass tags) was used to analyze the proteome in whole milk and skim milk to investigate the effect of skimming on milk proteins. A total of 1352 proteins were identified in whole milk and skim milk, and 199 differentially expressed proteins were screened. Compared with whole milk, 67 proteins were up-regulated and 132 proteins were down-regulated after defatting. Among the major active proteins in bovine milk, κ-casein decreased in relative content after defatting, while β-lactoglobulin and lactoferrin increased in relative content after defatting. α-lactalbumin, αs1-casein, αs2-casein, β-casein, bovine serum protein and lactoperoxidase did not differ significantly in relative content. The relative levels of butyrophilin and lactadherin in milk fat globule membrane proteins decreased after defatting. Skimming also had effects on cytoskeleton, metabolism-related proteins in milk, changing the quality and nutritional value of the milk. The analysis of protein in whole and skim milk clarified the effect of skimming on bovine milk protein, which could provide a reference for the development of infant dairy products and the purchase of milk with different fat content by consumers

Recent Progress on Biosensors Based on Nanomaterials for Detection of Food Allergens

Food allergy has become one of the prominent issues in the fields of food safety and public health. Since there is no effective treatment for food allergy, avoiding dietary exposure to (or intake of) food allergens based on label information should remain the best option for allergy sufferers. The development of sensitive, accurate and efficient allergen detection technologies is crucial for protecting consumers’ safety and rights. As a multidisciplinary detection technology, biosensors have the advantages of high specificity, quick response and easy operation. The rapid development of nanomaterials has advanced the development of highly sensitive and high-throughput biosensors for the visual detection of food allergens. In order to provide more references for further research and application of biosensors in food allergen detection, this paper summarizes the general situation of food allergen detection by biosensors, and analyzes the latest development of various biological recognition elements and biosensors based on different nanomaterials in the field of food allergen detection