Mode-superposition response spectrum method for wind-induced vibration analysis of structures

The calculation process of time history analysis method is complicated and time-consuming which is not convenient for wide application and promotion in engineering design. Based on the idea of mode decomposition in structural seismic response analysis, the fluctuating wind response spectrum and the mode decomposition response spectrum method for wind-induced vibration analysis are derived in this paper. Taking a high-rise building structure as an example, this paper uses the method proposed in this paper, the time history analysis method and the method of my country's load code to compare the wind-induced vibration response analysis. The results show that the method proposed in this paper is simple, effective and convenient for engineering application

A novel prognostic classification integrating lipid metabolism and immune co-related genes in acute myeloid leukemia

BackgroundAs a severe hematological malignancy in adults, acute myeloid leukemia (AML) is characterized by high heterogeneity and complexity. Emerging evidence highlights the importance of the tumor immune microenvironment and lipid metabolism in cancer progression. In this study, we comprehensively evaluated the expression profiles of genes related to lipid metabolism and immune modifications to develop a prognostic risk signature for AML.MethodsFirst, we extracted the mRNA expression profiles of bone marrow samples from an AML cohort from The Cancer Genome Atlas database and employed Cox regression analysis to select prognostic hub genes associated with lipid metabolism and immunity. We then constructed a prognostic signature with hub genes significantly related to survival and validated the stability and robustness of the prognostic signature using three external datasets. Gene Set Enrichment Analysis was implemented to explore the underlying biological pathways related to the risk signature. Finally, the correlation between signature, immunity, and drug sensitivity was explored.ResultsEight genes were identified from the analysis and verified in the clinical samples, including APOBEC3C, MSMO1, ATP13A2, SMPDL3B, PLA2G4A, TNFSF15, IL2RA, and HGF, to develop a risk-scoring model that effectively stratified patients with AML into low- and high-risk groups, demonstrating significant differences in survival time. The risk signature was negatively related to immune cell infiltration. Samples with AML in the low-risk group, as defined by the risk signature, were more likely to be responsive to immunotherapy, whereas those at high risk responded better to specific targeted drugs.ConclusionsThis study reveals the significant role of lipid metabolism- and immune-related genes in prognosis and demonstrated the utility of these signature genes as reliable bioinformatic indicators for predicting survival in patients with AML. The risk-scoring model based on these prognostic signature genes holds promise as a valuable tool for individualized treatment decision-making, providing valuable insights for improving patient prognosis and treatment outcomes in AML

mRNA vaccines in disease prevention and treatment

Abstract mRNA vaccines have emerged as highly effective strategies in the prophylaxis and treatment of diseases, thanks largely although not totally to their extraordinary performance in recent years against the worldwide plague COVID-19. The huge superiority of mRNA vaccines regarding their efficacy, safety, and large-scale manufacture encourages pharmaceutical industries and biotechnology companies to expand their application to a diverse array of diseases, despite the nonnegligible problems in design, fabrication, and mode of administration. This review delves into the technical underpinnings of mRNA vaccines, covering mRNA design, synthesis, delivery, and adjuvant technologies. Moreover, this review presents a systematic retrospective analysis in a logical and well-organized manner, shedding light on representative mRNA vaccines employed in various diseases. The scope extends across infectious diseases, cancers, immunological diseases, tissue damages, and rare diseases, showcasing the versatility and potential of mRNA vaccines in diverse therapeutic areas. Furthermore, this review engages in a prospective discussion regarding the current challenge and potential direction for the advancement and utilization of mRNA vaccines. Overall, this comprehensive review serves as a valuable resource for researchers, clinicians, and industry professionals, providing a comprehensive understanding of the technical aspects, historical context, and future prospects of mRNA vaccines in the fight against various diseases

Design and Analysis of a Novel 2-DOF Rotation–Translation Precision Positioning Stage

This paper presents the design, modeling, simulation, and experimental testing of a novel 2-DOF precision micro-positioning stage. A compact parallel structure is proposed and the rotation stroke of the stage is improved by reducing the rotation radius. Compared with other positioning stages, the developed stage has the advantage of large rotation stroke, compact structure, and high resonant frequency, and it can realize various positioning functions with fewer piezoelectric actuators. The simplified flexibility equation of the composite bridge mechanism was obtained through the equivalent replacement of the composite hinge, and then the transmission ratio and input stiffness analysis model of the stage are further established. Then, the simulation and experiment verify the accuracy of the model. The significant size parameters of the stage are determined according to the sensitivity analysis and verified by FEA. To decouple the rotation and translation, we establish the scale factor. The experimental results reveal that the workspace of the stage is 22.90 mrad × 95.03 μm. The step response time is 80 ms and the rotation resolution is 5 μrad under open-loop control

The 5-Aminolevulinic Acid (5-ALA) Supplement Enhances PSII Photochemical Activity and Antioxidant Activity in the Late Growth Promotion of Pseudostellaria heterophylla

This study focused on the physiological regulation and mechanism of exogenous 5-aminolevulinic acid (5-ALA) in the late growth of P. heterophylla. In the middle of May, different concentrations of 5-ALA (0, 10, 20, 50 mg·L−1) were sprayed on the leaves. The effects of 5-ALA on tuberous root growth, antioxidant enzyme system, gas exchange, photosynthetic pigment contents and photosynthetic characteristics were measured from 23 May to 13 June. A concentration of 20 mg·L−1 of 5-ALA led to a significant increase in the yield of fresh root and biomass allocation at 38.12% and 25.07%, respectively, in comparation with the control (0 mg·L−1). The moderate concentration of 5-ALA statistically stimulated antioxidation activities. 5-ALA treatment enhanced photosynthetic activity and reduced photodamage. Compared to the control, there were increases in the chlorophyll fluorescence parameters of P. heterophylla under 5-ALA treatment. Moreover, 20 mg·L−1 of 5-ALA significantly changed the kinetic parameters of fluorescence. It enhanced the light absorption and distribution efficiency of PSII and the activities of leaves, resulting in alleviating photoinhibition by the excess excitation energy. The correlation indicated that there was a significant positive correlation between the yield of tuberous roots and biomass allocation, Pn and catalase (CAT), and a negative correlation between the yield of tuberous roots and malondialdehyde (MDA). The appropriate 5-ALA concentration in the late growth stage of P. heterophylla effectively enhanced the net photosynthetic capacity, mainly resulting from the enhancement of PSII photochemical activity to promote the increases in excitation energy absorption, capture and electron transfer efficiency of the leaves. Finally, 5-ALA treatment can increase the photochemical activity of PSII in the whole leaf and ultimately delay the senescence of P. heterophylla

QTL Detection and Elite Alleles Mining for Stigma Traits in Oryza sativa by Association Mapping

Stigma traits are very important for hybrid seed production in Oryza sativa, which is a self-pollinated crop; however, the genetic mechanism controlling the traits is poorly understood. In this study, we investigated the phenotypic data of 227 accessions across two years and assessed their genotypic variation with 249 simple sequence repeat (SSR) markers. By combining phenotypic and genotypic data, a genome-wide association (GWA) map was generated. Large phenotypic variations in stigma length (STL), stigma brush-shaped part length (SBPL) and stigma non-brush-shaped part length (SNBPL) were found. Significant positive correlations were identified among stigma traits. In total, 2,072 alleles were detected among 227 accessions, with an average of 8.3 alleles per SSR locus. GWA mapping detected 6 quantitative trait loci (QTLs) for the STL, 2 QTLs for the SBPL and 7 QTLs for the SNBPL. Eleven, 5, and 12 elite alleles were found for the STL, SBPL and SNBPL, respectively. Optimal cross designs were predicted for improving the target traits. The detected genetic variation in stigma traits and QTLs provides helpful information for cloning candidate STL genes and breeding rice cultivars with longer STLs in the future

Fatigue life prediction based on a deep learning method for Ti-6Al-4V fabricated by laser powder bed fusion up to very-high-cycle fatigue regime

Microstructural defects and inhomogeneity of titanium alloys fabricated by laser powder bed fusion (LPBF) make their fatigue behaviors much more complicated than the conventionally made ones, especially in very-high-cycle fatigue (VHCF) regime. Most of traditional models/formulae and currently-used machine learning algorithms mainly concern fatigue behavior of LPBF-fabricated titanium alloys in high-cycle fatigue (HCF) regime, but rarely in VHCF regime. In this paper, a deep belief neural network-back propagation (DBN-BP) model was proposed to predict the fatigue life of LPBF-fabricated Ti-6Al-4V up to VHCF regime. Results obtained in this study indicate that the DBN-BP model exhibits high precision and strong stability in predicting the fatigue life of LPBFfabricated Ti-6Al-4V in both HCF and VHCF regimes. The primary hyperparameters of the DBN-BP model were optimized to further improve the prediction precision of this innovative model. Finally, the optimal DBN-BP model was applied to predict the relation between mean stress and stress amplitude, and the effect of energy density on the fatigue behavior of LPBF-fabricated Ti-6Al-4V up to VHCF regime

The level of lipopolysaccharide-binding protein is elevated in adult patients with obstructive sleep apnea

Abstract Background lipopolysaccharide-binding protein (LBP) has been to be a surrogate marker of inflammation in OSA. This study aimed to test the hypothesis that the concentration of LBP is elevated in adult patients with obstructive sleep apnea (OSA). Methods A total of 90 patients were enrolled into the study, 50 subjects were divided into OSA groups and 40 in healthy control according to PSG examination. Subsequently, patients with apnea-hypopnea index (AHI) ≧ 5, were divided into different subgroups according to blood pressure, gender, body mass index (BMI) and AHI. Venous blood samples were collected for detection after polysomnography. The serum levels of LBP and proinflammatory cytokines (interleukin (IL)-1β, IL-6, tumor necrosis factor (TNF)-α) were tested by ELISA. Results The present study demonstrated that the serum levels of both LBP and proinflammatory cytokines were elevated in OSA patients. A stratified analysis conducted to analyze differences among subgroups indicated that OSA patients with a higher AHI or BMI had an increased level of LBP and proinflammatory cytokines (all p < 0.05). Furthermore, a significant correlations were observed between LBP and inflammation and AHI. Multivariate regression analysis also demonstrated that AHI, LSaO2 and BMI had impact on the concentration of LBP. Conclusion The research showed that the serum level of LBP and proinflammatory cytokines were elevated in adult patients with OSA, and an association with severity of disease and BMI were established. Furthermore, sleep apnea and BMI had effect on the concentration of LBP

Automatic counting methods in aquaculture: a review

Object counting in aquaculture is an important task, and has been widely applied on fish population estimation, lobster abundance estimation, and scallop stock, etc. However, underwater object counting is challenging for biologists and marine scientists, because of the diversity of background of the lake or ocean, the uncertainty of the object motion, and the occlusion between objects. With the rapid development of sensor, computer vision and acoustic technologies, advanced and efficient counting methods are available in aquaculture. We reviewed underwater object counting methods in aquaculture, provided a survey including more than 50 papers in the recent 10 years, and analyzed the pros and cons of the counting methods and the applicable scenarios of those methods. Finally, the major challenges and future trends of underwater object counting in aquaculture are discussed