Network Optimization of CNT Yarn Sensor Based on NNIA Algorithm in Damage Monitoring of 3D Braided Composites.

In order to solve the optimization problem of carbon nanotube (CNT) yarn sensor network embedded in three-dimensional (3D) braided composite materials and realize the structural health monitoring of internal damage of aerospace parts, the multi-objective optimization of the number and location of sensors was studied using non-dominated neighborhood immune algorithm (NNIA). Through the research of 3D six-direction braiding process, stress sensitivity of single CNT yarn sensor, and damage location of 3D braided composites, the number, position, and coverage constraint functions based on NNIA algorithm are constructed. In addition, the number and position of three-dimensional braided composite embedded CNT yarn sensors with different sizes are solved. Through the stress experiment and data analysis of damaged parts, it is proved that the optimized configuration result of CNT yarn sensor obtained by NNIA algorithm is suitable for the damage monitoring of 3D braided composites. The damage location error is less than 1 mm. This study lays a foundation for the establishment of damage source localization model of 3D braided composites.

Changes in chemical composition, structural and functional microbiome during alfalfa (Medicago sativa) ensilage with Lactobacillus plantarum PS-8.

Improving silage production by adding exogenous microorganisms not only maximizes nutrient preservation, but also extends product shelf life. Herein, changes in the quality and quantity of Lactobacillus plantarum PS-8 (PS-8) -inoculated alfalfa (Medicago sativa) during silage fermentation were monitored at d 0, 7, 14, and 28 (inoculum dose of PS-8 was 1 × 105 colony forming units [cfu]/g fresh weight; 50 kg per bag; 10 bags for each time point) by reconstructing metagenomic-assembled genomes (MAG) and Growth Rate InDex (GRiD). Our results showed that the exogenous starter bacterium, PS-8 inoculation, became the most dominating strain by d 7, and possibly played a highly active role throughout the fermentation process. The pH value of the silage decreased greatly, accompanied by the growth of acid-producing microorganisms namely PS-8, which inhibited the growth of harmful microorganisms like molds (4.18 vs. 1.42 log cfu/g) and coliforms (4.95 vs. 0.66 log most probable number [MPN]/g). The content of neutral detergent fiber (NDF) decreased significantly (41.6% vs. 37.6%; dry matter basis). In addition, the abundance and diversity of genes coding microbial carbohydrate-active enzymes (CAZymes) increased significantly and desirably throughout the fermentation, particularly the genes responsible for degrading starch, arabino-xylan, and cellulose. Overall, our results showed that PS-8 was replicating rapidly and consistently during early- and mid-fermentation phases, promoting the growth of beneficial lactic acid bacteria and inhibiting undesirable microbes, ultimately improving the quality of silage.

Changes in physico-chemical characteristics and viable bacterial communities during fermentation of alfalfa silages inoculated with Lactobacillus plantarum.

This study investigated the effect of inoculating Lactobacillus (L.) plantarum PS-8 in fermentation of alfalfa silages. We monitored the fermentation characteristics and bacterial population dynamics during the ensiling process. PacBio single molecule real time sequencing was combined with propidium monoazide (PMA) treatment to monitor the viable microbiota dynamics. We found that inoculating L. plantarum PS-8 may improve the silage quality by accelerating acidification, reducing the amounts of clostridia, coliform bacteria, molds and yeasts, elevating the protein and organic acid contents (except butyrate), and enhancing lactic acid bacteria (LAB) while suppressing harmful microorganisms. Some significant differential abundant taxa were found between the PMA-treated and non-treated microbiota. For example, the relative abundances of L. brevis, L. plantarum, and Pediococcus pentosaceus were significantly higher in the PMA-treated group than the non-PMA-treated group, suggesting obvious differences between the viable and non-viable microbiota. It would thus be necessary to distinguish between the viable and non-viable microbial communities to further understand their physiological contribution in silage fermentation. By tracking the dynamics of viable microbiota in relation with changes in the physico-chemical parameters, our study provided novel insights into the beneficial effects of inoculating L. plantarum PS-8 in silage fermentation and the physiological function of the viable bacterial communities.

Assessing quality of Medicago sativa silage by monitoring bacterial composition with single molecule, real-time sequencing technology and various physiological parameters.

The present study applied the PacBio single molecule, real-time sequencing technology (SMRT) in evaluating the quality of silage production. Specifically, we produced four types of Medicago sativa silages by using four different lactic acid bacteria-based additives (AD-I, AD-II, AD-III and AD-IV). We monitored the changes in pH, organic acids (including butyric acid, the ratio of acetic acid/lactic acid, γ-aminobutyric acid, 4-hyroxy benzoic acid and phenyl lactic acid), mycotoxins, and bacterial microbiota during silage fermentation. Our results showed that the use of the additives was beneficial to the silage fermentation by enhancing a general pH and mycotoxin reduction, while increasing the organic acids content. By SMRT analysis of the microbial composition in eight silage samples, we found that the bacterial species number and relative abundances shifted apparently after fermentation. Such changes were specific to the LAB species in the additives. Particularly, Bacillus megaterium was the initial dominant species in the raw materials; and after the fermentation process, Pediococcus acidilactici and Lactobacillus plantarum became the most prevalent species, both of which were intrinsically present in the LAB additives. Our data have demonstrated that the SMRT sequencing platform is applicable in assessing the quality of silage.

Complete genome sequence of Bacillus licheniformis BL-09, a probiotic strain isolated from naturally fermented congee.

Bacillus licheniformis BL-09 is a probiotic strain isolated from naturally fermented congee in Inner Mongolia of China. The genome of this strain contains a 4.39 Mb circular chromosome with an average GC content of 45.9%. The analysis of the genome revealed two gene clusters that are related to the peptide biosynthesis. The available genetic information of these peptides makes it possible to construct an improved strain for the industrial production of antimicrobial agents.