Cooperative Optimization QoS Cloud Routing Protocol Based on Bacterial Opportunistic Foraging and Chemotaxis Perception for Mobile Internet

In order to strengthen the mobile Internet mobility management and cloud platform resources utilization, optimizing the cloud routing efficiency is established, based on opportunistic bacterial foraging bionics, and puts forward a chemotaxis perception of collaborative optimization QoS (Quality of Services) cloud routing mechanism. The cloud routing mechanism is based on bacterial opportunity to feed and bacterial motility and to establish the data transmission and forwarding of the bacterial population behavior characteristics. This mechanism is based on the characteristics of drug resistance of bacteria and the structure of the field, and through many iterations of the individual behavior and population behavior the bacteria can be spread to the food gathering area with a certain probability. Finally, QoS cloud routing path would be selected and optimized based on bacterial bionic optimization and hedge mapping relationship between mobile Internet node and bacterial population evolution iterations. Experimental results show that, compared with the standard dynamic routing schemes, the proposed scheme has shorter transmission delay, lower packet error ratio, QoS cloud routing loading, and QoS cloud route request overhead

Detection of Lipase Activity Based on Fluorescence Inner Filter Effect of p-Nitrophenol

Lipase activity was detected based on the fluorescence properties of gold nanoclusters (AuNCs) and the inner filter effect (IFE) of p-nitrophenol. Glutathione-modified AuNCs was used as fluorophore, and p-nitrophenol produced from the lipase-catalyzed hydrolysis of p-nitrophenol palmitate as fluorescence absorbent. The results showed that under the optimal conditions (p-nitrophenyl palmitate concentration 1.6 mg/mL, pH 7.5, temperature 50 ℃, and reaction time 20 min), the relative fluorescence intensity (F0–F, y) was positively correlated with lipase activity (x) in the range of 5.6–196 U/L, which was described by the equation y = 2.003 5 + 0.936 8x, with a correlation coefficient (r2) of 0.997 8, and the detection limit was 1.3 U/L (at a signal-to-noise ratio of 3). The developed method is simple and sensitive, and can be applied to the detection of lipase activity

Identification of stable reference genes for quantitative gene expression analysis in the duodenum of meat-type ducks

Quantitative polymerase chain reaction (qPCR) is an important method to detect gene expression at the molecular level. The selection of appropriate housekeeping genes is the key to accurately calculating the expression level of target genes and conducting gene function studies. In this study, the expression of eight candidate reference genes, glyceraldehyde-3-phosphate dehydrogenase (GAPDH), beta-actin (β-actin), 18S ribosomal RNA (18S rRNA), hydroxymethylbilane synthase (HMBS), hypoxanthine phosphoribosyltransferase 1 (HPRT1), TATA box binding protein (TBP), ribosomal protein L13 (RPL13), and tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein (YWHAZ), in the duodenal epithelial tissue of 42-day-old meat-type ducks were detected using qPCR. Furthermore, their expression stability was analyzed using the geNorm, NormFinder, and BestKeeper programs. The results indicated that HMBS and YWHAZ were the most stably expressed genes. All three programs indicated that the expression of 18S rRNA was the least stable, making it unsuitable for the study of gene expression in meat-type duck tissues. This study provides stable reference genes for gene expression analysis and contributes to further studies on the gene function of meat-type ducks

Cooperative Optimization QoS Cloud Routing Protocol Based on Bacterial Opportunistic Foraging and Chemotaxis Perception for Mobile Internet

In order to strengthen the mobile Internet mobility management and cloud platform resources utilization, optimizing the cloud routing efficiency is established, based on opportunistic bacterial foraging bionics, and puts forward a chemotaxis perception of collaborative optimization QoS (Quality of Services) cloud routing mechanism. The cloud routing mechanism is based on bacterial opportunity to feed and bacterial motility and to establish the data transmission and forwarding of the bacterial population behavior characteristics. This mechanism is based on the characteristics of drug resistance of bacteria and the structure of the field, and through many iterations of the individual behavior and population behavior the bacteria can be spread to the food gathering area with a certain probability. Finally, QoS cloud routing path would be selected and optimized based on bacterial bionic optimization and hedge mapping relationship between mobile Internet node and bacterial population evolution iterations. Experimental results show that, compared with the standard dynamic routing schemes, the proposed scheme has shorter transmission delay, lower packet error ratio, QoS cloud routing loading, and QoS cloud route request overhead

Spatial Load Prediction Considering Spatiotemporal Distribution of Electric Vehicle Charging Load

In view of the influence of large-scale electric vehicle access to the distribution network on spatial load prediction, this paper proposes a spatial load prediction method for urban distribution network considering the spatial and temporal distribution of electric vehicle charging load. Firstly, electric vehicles are classified according to charging mode and travel characteristics of various types of vehicles. Secondly, the probability distribution function is fitted to the travel rules of electric vehicles according to the travel survey and statistical data of residents. Then, the model of electric vehicle travel chain is constructed, and the charging load in different regions and different times is calculated by Monte Carlo method. Finally, based on the actual data of a certain area, the predicted spatial load values of different functional communities in one day are obtained, which can provide reference for future urban distribution network planning

Effect of Corn Starch Granules on Stabilizing the Foam Structure of Ultrasonically Modified Whey Isolate Protein

In this study, the mechanism of ultrasound combined with corn starch granules (CSG) treatment improved the foam properties of whey protein isolates (WPI) and was systematically investigated. The results showed that ultrasound combined with corn starch granules treatment increased foam capacity and stability by 15.38% and 41.40%, respectively. Compared with the control group, corn starch granules enhanced the surface charge (52.38%) and system turbidity (51.43%), which certainly provided the necessary conditions for the improvement of foam stabilization stability. In addition, corn starch granules as microgel particles increased the mechanical properties of the interfacial protein film, thus delaying the instability of foam. This research would provide new insights into the design of new protein-based foam foods in the future food industry

Insight into the Effect of Promoter Mn on Ethanol Formation from Syngas on a Mn-Promoted MnCu(211) Surface: A Comparison with a Cu(211) Surface

Density functional theory calculations have been employed to investigate the effect of promoter Mn on ethanol formation from syngas on a Mn-promoted MnCu(211) surface. Our results show that CO + 3H → CHO + 2H → CH₂O + H → CH₃O is an optimal pathway for the overall CO conversion. Starting with CH₃O, CH₃ is formed via CH₃O → CH₃ + O. Then, CHO insertion into CH₃ can form CH₃CHO, and further, CH₃CHO is successively hydrogenated to ethanol via CH₃CH₂O intermediate. Meanwhile, CH₃OH is formed via CH₃O + H → CH₃OH. Compared to the pure Cu(211) surface, CH₃ formation is found to be energetically compatible with CH₃OH formation on the MnCu(211) surface, which can lead to more CH₃ sources and less CH₃OH; thus, the productivity and selectivity of ethanol can be improved. On the other hand, starting from CH₃, the MnCu(211) surface is more favorable for CHO insertion into CH₃ to CH₃CHO in comparison with CH₃ hydrogenation, dissociation and coupling to CH₄, CH₂, and C₂H₆ due to their high activation barriers; namely, the MnCu(211) surface exhibits a better selectivity toward C₂ oxygenates rather than hydrocarbons. As a result, we can show that, by introducing promoter Mn into Cu catalyst, the productivity and selectivity to ethanol from syngas can be effectively improved