Earthquake Damage Assessment for RC Structures Based on Fuzzy Sets

A global damage index based on multiple linear force-deformation curves in pushover analysis is presented to evaluate the integrated damage of reinforced concrete structure. The modified coefficient is provided considering the cyclic load and hysteresis energy. The number of inelastic cycles and the coefficient of hysteresis energy concentration are also introduced as damage indices. Hence, multiple damage indices about displacement and energy for performance-based design are considered. The relation of multiple damage indices or factors and the fuzzy damage set is presented by comprehensive fuzzy evaluation; hence, a performance-based multiple fuzzy seismic damage-assessment method for reinforced concrete frame structures is established. The method can be accomplished based on pushover analysis, code spectrum, and capacity spectrum method. The fuzzy seismic damage-assessment method is verified through nonlinear analysis four different structures and the corresponding results and assessment conclusions are accurate

A novel molecular signature for predicting prognosis and immunotherapy response in osteosarcoma based on tumor-infiltrating cell marker genes

BackgroundTumor infiltrating lymphocytes (TILs), the main component in the tumor microenvironment, play a critical role in the antitumor immune response. Few studies have developed a prognostic model based on TILs in osteosarcoma.MethodsScRNA-seq data was obtained from our previous research and bulk RNA transcriptome data was from TARGET database. WGCNA was used to obtain the immune-related gene modules. Subsequently, we applied LASSO regression analysis and SVM algorithm to construct a prognostic model based on TILs marker genes. What’s more, the prognostic model was verified by external datasets and experiment in vitro. ResultsEleven cell clusters and 2044 TILs marker genes were identified. WGCNA results showed that 545 TILs marker genes were the most strongly related with immune. Subsequently, a risk model including 5 genes was developed. We found that the survival rate was higher in the low-risk group and the risk model could be used as an independent prognostic factor. Meanwhile, high-risk patients had a lower abundance of immune cell infiltration and many immune checkpoint genes were highly expressed in the low-risk group. The prognostic model was also demonstrated to be a good predictive capacity in external datasets. The result of RT-qPCR indicated that these 5 genes have differential expression which accorded with the predicting outcomes.ConclusionsThis study developed a new molecular signature based on TILs marker genes, which is very effective in predicting OS prognosis and immunotherapy response

COMT, 5-HTR2A, and SLC6A4 mRNA Expressions in First-Episode Antipsychotic-Naïve Schizophrenia and Association With Treatment Outcomes

Background: Dopaminergic and serotonergic systems play crucial roles in the pathophysiology of schizophrenia and modulate response to antipsychotic treatment. However, previous studies of dopaminergic and serotonergic genes expression are sparse, and their results have been inconsistent. In this longitudinal study, we aim to investigate the expressions of Catechol-O-methyltransferase (COMT), serotonin 2A receptor (5-HTR2A), and serotonin transporter gene (SLC6A4) mRNA in first-episode antipsychotic-naïve schizophrenia and to test if these mRNA expressions are associated with cognitive deficits and treatment outcomes or not.Method: We measured COMT, 5-HTR2A, and SLC6A4 mRNA expressions in 45 drug-naive first-episode schizophrenia patients and 38 health controls at baseline, and repeated mRNA measurements in all patients at the 8-week follow up. Furthermore, we also assessed antipsychotic response and cognitive improvement after 8 weeks of risperidone monotherapy.Results: Patients were divided into responders (N = 20) and non-responders groups (N = 25) according to the Remission criteria of the Schizophrenia Working Group. Both patient groups have significantly higher COMT mRNA expression and lower SLC6A4 mRNA expression when compared with healthy controls. Interestingly, responder patients have significantly higher levels of COMT and 5-HTR2A mRNA expressions than non-responder patients at baseline. However, antipsychotic treatment has no significant effect on the expressions of COMT, 5-HTR2A, and SLC6A4 mRNA over 8-week follow up.Conclusion: Our findings suggest that dysregulated COMT and SLC6A4 mRNA expressions may implicate in the pathophysiology of schizophrenia, and that COMT and 5-HTR2A mRNA may be potential biomarkers to predict antipsychotic response

Manipulating Protein Conformations By Single-molecule Afm-fret Nanoscopy

Combining atomic force microscopy and fluorescence resonance energy transfer spectroscopy (AFM-FRET), we have developed a single-molecule AFM-FRET nanoscopy approach capable of effectively pinpointing and mechanically manipulating a targeted dye-labeled single protein in a large sampling area and simultaneously monitoring the conformational changes of the targeted protein by recording single-molecule FRET time trajectories. We have further demonstrated an application of using this nanoscopy on manipulation of single-molecule protein conformation and simultaneous single-molecule FRET measurement of a Cy3-Cy5-labeled kinase enzyme, HPPK (6-hydroxymethyl-7,8-dihydropterin pyrophosphokinase). By analyzing time-resolved FRET trajectories and correlated AFM force pulling curves of the targeted single-molecule enzyme, we are able to observe the protein conformational changes of a specific coordination by AFM mechanic force pulling

Reliability of neuroanatomical measurements in a multi-site longitudinal study of youth at risk for psychosis

Multi-site longitudinal neuroimaging designs are used to identify differential brain structural change associated with onset or progression of disease. The reliability of neuroanatomical measurements over time and across sites is a crucial aspect of power in such studies. Prior work has found that while within-site reliabilities of neuroanatomical measurements are excellent, between-site reliability is generally more modest. Factors that may increase between-site reliability include standardization of scanner platform and sequence parameters and correction for between-scanner variations in gradient nonlinearities. Factors that may improve both between- and within-site reliability include use of registration algorithms that account for individual differences in cortical patterning and shape. In this study 8 healthy volunteers were scanned twice on successive days at 8 sites participating in the North American Prodrome Longitudinal Study (NAPLS). All sites employed 3 Tesla scanners and standardized acquisition parameters. Site accounted for 2 to 30% of the total variance in neuroanatomical measurements. However, site-related variations were trivial (<1%) among sites using the same scanner model and 12-channel coil or when correcting for between-scanner differences in gradient nonlinearity and scaling. Adjusting for individual differences in sulcal-gyral geometries yielded measurements with greater reliabilities than those obtained using an automated approach. Neuroimaging can be performed across multiple sites at the same level of reliability as at a single site, achieving within- and between-site reliabilities of 0.95 or greater for gray matter density in the majority of voxels in the prefrontal and temporal cortical surfaces as well as for the volumes of most subcortical structures

Constitutive Relation of Engineering Material Based on SIR Model and HAM

As an epidemic mathematical model, the SIR model represents the transition of the Susceptible, Infected, and Recovered. The profound implication of the SIR model is viewed as the propagation and dynamic evolutionary process of the different internal components and the characteristics in a complex system subject to external effect. The uniaxial stress-strain curve of engineering material represents the basic constitutive relation, which also represents the damage propagation in the units of the damaged member. Hence, a novel dynamic stress-strain model is established based on the SIR model. The analytical solution and the approximate solution for the proposed model are represented according to the homotopy analysis method (HAM), and the relationship of the solution and the size effect and the strain rate is discussed. In addition, an experiment on the size effect of confined concrete is carried out and the solution of SIR model is suitable for simulation. The results show that the mechanical mechanism of the parameters of the uniaxial stress-strain model proposed in this paper reflects the actual characteristics of the materials. The solution of the SIR model can fully and accurately show the change of the mechanical performance and the influence of the size effect and the strain rate

Double-Stack Aggregation Network Using a Feature-Travel Strategy for Pansharpening

Pansharpening methods based on deep learning can obtain high-quality, high-resolution multispectral images and are gradually becoming an active research topic. To combine deep learning and remote sensing domain knowledge more efficiently, we propose a double-stack aggregation network using a feature-travel strategy for pansharpening. The proposed network comprises two important designs. First, we propose a double-stack feature aggregation module that can efficiently retain useful feature information by aggregating features extracted at different levels. The module introduces a new multiscale, large-kernel convolutional block in the feature extraction stage to maintain the overall computational power while expanding the receptive field and obtaining detailed feature information. We also introduce a feature-travel strategy to effectively complement feature details on multiple scales. By resampling the source images, we use three pairs of source images at various scales as the input to the network. The feature-travel strategy lets the extracted features loop through the three scales to supplement the effective feature details. Extensive experiments on three satellite datasets show that the proposed model achieves significant improvements in both spatial and spectral quality measurements compared to state-of-the-art methods