"Hang" and "Crash" in Fault Analysis of Philips HD Series Color Doppler Ultrasound in Summary of Medical Equipment Maintenance Experience

Color doppler ultrasound is an important imaging equipment to examine systemic diseases in hospital.Over the past years, the Philips HD series ultrasound system have attracted great attention for their outstanding imaging ability. This paper introduce the structure principle of HD series ultrasound system,and introduces the difference and different troubleshooting methods when HD color doppler ultrasound system displays' Hang 'and' Crash 'faults

Research on Shear Lag Effect of T-shaped Short-leg Shear Wall

Longitudinal displacement of cross section of T-shaped shortlegshear wall was simplified to three parts: shear lag warpingdisplacement, plane section bending displacement and axialdisplacement. Shear lag warping deformation was assumed ascubic parabola distribution along flange, and based on minimumpotential energy principle, differential equations were deduced;with boundary conditions, a calculation theory for shear lageffect was established. With two T-shaped short-leg shear wallmodels, vertical stresses of flanges were obtained by calculationtheory and finite element calculation respectively, and comparisonbetween theoretical analysis results and numerical calculationresults was made. At last, parameter analysis was carriedout, and the influence of shear force, shear span ratio andheight-thickness ratio on shear lag coefficient was obtained.Research shows that numerical calculation results are in goodagreement with theoretical analysis results, and each parameterhas different influence on shear lag coefficient

MiR-486 protects against acute myocardial infarction via regulation of PTEN

Purpose: To investigate the effect of miR-486 on rats with acute myocardial infarction (AMI), and its mechanism of action.Methods: A rat model of AMI was established. They were randomly divided into 4 groups, namely, sham, model, agomiR-486 and antagomiR-486 groups, respectively. Rats in these different groups were treated with agomiR-21 (5 μL, 40 nmol/mL), antagomiR-21 (5 μL, 40 nmol/mL) or agomiR-NC (5 μL, 40 nmol/mL), respectively. Then, key miRNAs were sorted out using gene-chip assay and verified by quantitative reverse transcription polymerase chain reaction (qRT-PCR) assay. Luciferase reporter gene assay was conducted to determine the interaction between miR-486 and gene of PTEN. After intraperitoneal injection of agomiR-486 and antagomiR-486, hemodynamics was measured to determine the effect of miR-486 on myocardial function of the rats. The effect of miR-486 expression level on the expression of myocardial enzymes in serum, the morphology of myocardial tissues, and the apoptosis of myocardial tissues in rats, were investigated. Additionally, the effect of miR-486 expression level on PTEN/AKT signaling pathway in the rats was determined by Western blotting.Results: The results of gene-chip and qRT-PCR assays revealed that there were 8 differentially expressed genes in rat myocardial tissues in the model group when compared with the sham group. MiR-486 improved the cardiac function of rats and the morphology of myocardial tissues, but reduced AMI-induced apoptosis of myocardial cells and the expression of myocardial enzymes (markers of myocardial injury) in a dose-dependent manner (p < 0.05). The results of luciferase reporter gene assay showed that PTEN was a direct target of miR-486. In rat models of AMI, a raised expression of miR-486 remarkably suppressed the protein expression level of PTEN and up-regulated that of p-AKT/AKT (p < 0.05).Conclusion: MiR-486 protects against AMI in rats probably by targeting PTEN and activating the AKT signaling pathway. The results of the current study may provide new insights for the treatment of AMI

Identifying Latent Causal Content for Multi-Source Domain Adaptation

Multi-source domain adaptation (MSDA) learns to predict the labels in target domain data, under the setting that data from multiple source domains are labelled and data from the target domain are unlabelled. Most methods for this task focus on learning invariant representations across domains. However, their success relies heavily on the assumption that the label distribution remains consistent across domains, which may not hold in general real-world problems. In this paper, we propose a new and more flexible assumption, termed \textit{latent covariate shift}, where a latent content variable $\mathbf{z}_c$ and a latent style variable $\mathbf{z}_s$ are introduced in the generative process, with the marginal distribution of $\mathbf{z}_c$ changing across domains and the conditional distribution of the label given $\mathbf{z}_c$ remaining invariant across domains. We show that although (completely) identifying the proposed latent causal model is challenging, the latent content variable can be identified up to scaling by using its dependence with labels from source domains, together with the identifiability conditions of nonlinear ICA. This motivates us to propose a novel method for MSDA, which learns the invariant label distribution conditional on the latent content variable, instead of learning invariant representations. Empirical evaluation on simulation and real data demonstrates the effectiveness of the proposed method