Risk factor analysis for adverse prognosis of the fetal ventricular septal defect (VSD).

BACKGROUND: Ventricular septal defect (VSD) is the most common subtype of congenital heart disease. In the present study, we aimed to determine whether chromosome aberration was associated with the occurrence of VSD and evaluate the association of VSD size, location and chromosome aberration with adverse outcomes in the Chinese fetuses. METHODS: Fetuses with VSD and comprehensive follow-up data were included and evaluated retrospectively. Medical records were used to collect epidemiological data and foetal outcomes. For VSD fetuses, conventional karyotype and microarray analysis were conducted. After adjusting confounding factors by using multivariable logistic regression analyses, the association between chromosome variations and VSD occurrence was explored. The association between defect size, location and chromosome aberrations and adverse foetal outcomes was also investigated. RESULTS: Chromosome aberration was the risk factor for VSD occurrence, raising 6.5-fold chance of developing VSD. Chromosome aberration, peri-membranous site and large defect size of VSD were significant risk factors of adverse fetal outcome. Chromosome aberrations, including pathogenic copy number variations (CNVs) and variations of uncertain significance (VUS), were both risk factors, increasing the risk of the adverse fetal outcome by 55.9 times and 6.7 times, respectively. The peri-membranous site would increase 5.3-fold risk and defects larger than 5 mm would increase the 7.1-fold risk for poor fetal outcome. CONCLUSIONS: The current investigation revealed that chromosomal abnormalities, large defects, and the peri-membranous site were all risk factors for poor fetal outcomes. Our study also indicated that chromosome aberration was one of risk factors for the VSD occurrence.

A New Probabilistic Ellipse Imaging Method Based on Adaptive Signal Truncation for Ultrasonic Guided Wave Defect Localization on Pressure Vessels.

Pressure vessels are prone to defects due to environmental conditions, which may cause serious safety hazards to industrial production. The probabilistic ellipse imaging method, based on ultrasonic guided wave, is a common method for locating defects on plate-like structures. In this paper, the research showed that the accuracy of the traditional probabilistic ellipse imaging method was severely affected by the truncation length of the signal. In order to improve the defect location accuracy of the probabilistic elliptic imaging algorithm, an adaptive signal truncation method based on signal difference analysis was proposed, and a novel probabilistic elliptic imaging method was developed. Firstly, the relationship model between the signal difference coefficient (SDC) and the distance coefficient was constructed. Through this model, the distance coefficient of each group signal can be calculated, so that the adaptive truncation length for each group of signals can be determined and the truncated signals used for defect imaging. Secondly, in order to improve the robustness of the new imaging method, the relationship between the defect location accuracy and SDC thresholds were investigated and the optimal threshold was determined. The experimental results showed that the probabilistic ellipse imaging algorithm, based on the new adaptive signal truncation method, can effectively locate a single defect on a pressure vessel.

Defect Detection Method for CFRP Based on Line Laser Thermography.

A continuous line laser scanning inspection technique for tracing load-bearing structures was developed and applied to defect detection of unidirectional carbon-fiber-reinforced polymers for aero engines. The heat transfer model of the material was analyzed using the finite element software COMSOL. Meanwhile, a laser platform was built and an image algorithm was used to verify the feasibility of the method. The potential of this technique for detecting defects and providing information on the location of defects in carbon fiber composites was analyzed. Results indicate line laser thermal imaging can successfully determine the size, location, and crack angle of surface damage with extremely high accuracy. The positioning accuracy error for impact and fracture defects is less than 20%, and the detection rate can reach 100% if the defect is in the special position of just leaving the heating area. The angle detection of fracture cracks can be accurate within 10°.

Influence of defect locations and nitrogen doping configurations on the mechanical properties of armchair graphene nanoribbons.

The effect of defect locations on the mechanical properties of armchair graphene nanoribbons (AGNRs) and the various configurations of nitrogen (N) doping on the mechanical properties of AGNRs were examined using molecular dynamics (MD) simulations. The variation of the Young's modulus (YM) and the ultimate tensile strength (UTS) of pyridinic-N, graphitic-N, and pyrrolic-N by increasing the concentration of N doping was investigated. The results of MD simulations show that the defect location has a significant effect on the UTS and failure strain (FS) of AGNRs in both vertical and horizontal directions. In the horizontal direction, variations of the UTS and FS are lower than in the vertical direction. On the other hand, the variations of the YM is almost similar in vertical and horizontal directions. The results of this work indicate that the UTS and FS of AGNRs are more sensitive than the YM of AGNRs for different defect directions. Pyridinic-N improves the mechanical properties of the defective AGNR and performs better YM and UTS values than the graphitic-N. Substitution N atoms, which are located at the defective sites and/or at the edges of AGNRs, are mechanically more favorable. Pyrrolic-N configuration has the lowest mechanical properties among the other configurations. Furthermore, pyrrolic-N with Stone-Wales-1 (SW-1) type of defect has higher mechanical properties than pyrrolic-N with Stone-Wales-2 (SW-2) type of defect.

Wavelet transform-based electron tomography measurement of buried interface roughness.

Interface roughness is a critical parameter determining the performance of semiconductor devices. We show that a continuous wavelet transform is useful to describe not only the magnitude of the interface roughness, but also the spatial frequencies that describe the interface. We propose a simple presentation of the results that makes it convenient to compare between interfaces. In particular, an average and maximum value wavelet profile that is obtained from a series of one dimensional wavelet transforms provides a traceable and quick survey of the results. We demonstrate the wavelet transform method using both computer simulations and by applying it to experimental data obtained by electron tomography of a test sample and to a molecular layer interface. Wavelet descriptions of the interface roughness suffers less from the presence of shot noise in the experimental data than the traditional root mean square error description of interface roughness. An increase in lateral dimensions of an interface that has large features increases the content of low spatial frequencies in wavelet transforms. In comparison, the value of root mean square error increases in an untraceable manner with the same increase in lateral dimensions on the same interface. Morse wavelets with γ = 9 and ß = 3 appear to be a suitable choice for applications in interface roughness measurement.