RESUMO
An Aquila optimizer-back propagation (AO-BP) neural network was used to establish an approximate model of the relationship between the design variables and the optimization objective to improve elevator block brake capabilities and achieve a lightweight brake design. Subsequently, the constraint conditions and objective functions were determined. Moreover, the multi-objective genetic algorithm optimized the structural block brake design. Finally, the effectiveness of the optimization results was verified using simulation experiments. The results demonstrate that the maximum temperature of the optimized brake wheel during emergency braking was 222.09°C, which is 36.71°C lower than that of 258.8°C before optimization, with a change rate of 14.2%. The maximum equivalent stress after optimization was 246.89 MPa, 28.87 MPa lower than that of 275.66 MPa before optimization, with a change rate of 10.5%. In addition, the brake wheel mass was reduced from 58.85 kg to 52.40 kg, and the thermal fatigue life at the maximum equivalent stress increased from 64 times before optimization to 94 times after optimization.
Assuntos
Elevadores e Escadas Rolantes , Redes Neurais de Computação , Simulação por ComputadorRESUMO
The 2-hydroxy-4-(methylthio) butanoic acid isopropyl ester (HMBi), a rumen protective methionine, has been extensively studied in dairy cows and beef cattle and has been shown to regulate gastrointestinal microbiota and improve production performance. However, knowledge of the application of HMBi on cashmere goats and the simultaneous study of rumen and hindgut microbiota is still limited. In this study, HMBi supplementation increased the concentration of total serum protein, the production of microbial protein in the rumen and feces, as well as butyrate production in the feces. The results of PCoA and PERMANOVA showed no significant difference between the rumen microbiota, but there was a dramatic difference between the fecal microbiota of the two groups of Cashmere goats after the HMBi supplementation. Specifically, in the rumen, HMBi significantly increased the relative abundance of some fiber-degrading bacteria (such as Fibrobacter) compared with the CON group. In the feces, as well as a similar effect as in the rumen (increasing the relative abundance of some fiber-degrading bacteria, such as Lachnospiraceae FCS020 group and ASV32), HMBi diets also increased the proliferation of butyrate-producing bacteria (including Oscillospiraceae UCG-005 and Christensenellaceae R-7 group). Overall, these results demonstrated that HMBi could regulate the rumen and fecal microbial composition of Liaoning cashmere goats and benefit the host.
Assuntos
Ésteres , Microbiota , Animais , Bovinos , Feminino , Ácido Butírico/farmacologia , Ácido Butírico/metabolismo , Ésteres/metabolismo , Rúmen/microbiologia , Fermentação , Cabras , Dieta/veterinária , Fezes , Bactérias/metabolismo , Suplementos Nutricionais , Ração Animal/análise , Lactação/fisiologiaRESUMO
Postmenopausal osteoporosis is the most common type of osteoporosis in women. To date, little is known about their transcriptome signatures, although biomarkers from peripheral blood mononuclear cells are attractive for postmenopausal osteoporosis diagnoses. Here, we performed bulk RNA sequencing of 206 samples (124 postmenopausal osteoporosis and 82 normal samples) and described the clinical phenotypic characteristics of postmenopausal women. We then highlighted the gene set enrichment analyses between the extreme T-score group and the heathy control group, revealing that some immune-inflammatory responses were enhanced in postmenopausal osteoporosis, with representative pathways including the mitogen-activated protein kinase (NES = 1.6, FDR <0.11) pathway and B_CELL_RECEPTOR (NES = 1.69, FDR <0.15) pathway. Finally, we developed a combined risk prediction model based on lasso-logistic regression to predict postmenopausal osteoporosis, which combined eleven genes (PTGS2, CXCL16, NECAP1, RPS23, SSR3, CD74, IL4R, BTBD2, PIGS, LILRA2, MAP3K11) and three pieces of clinical information (age, procollagen I N-terminal propeptide, ß isomer of C-terminal telopeptide of type I) and provided the best prediction ability (AUC = 0.97). Taken together, this study filled a gap in the large-scale transcriptome signature profiles and revealed the close relationship between immune-inflammatory responses and postmenopausal osteoporosis, providing a unique perspective for understanding the occurrence and development of postmenopausal osteoporosis.