Solid rocket motor propellant health monitoring based on oxide-doped curved long-period fiber grating.

A kind of curved long-period fiber grating(CLPFG) engraved by CO2 laser based on oxide-doped fiber was designed to monitor the structural integrity of propellant. The mechanical damage characteristics of the propellant were analyzed. The sensor model is constructed and the refractive index modulation characteristics of the CLPFG are analyzed. The strain coupling characteristics and the strain transfer efficiency of the interface between the CLPFG and the propellant are clarified. Propellant modules with implanted CLPFG were fabricated. The novel grating sensor has been effectively coated and structurally packaged. Conducted experiments on strain and temperature of propellant modules. The large strain measurement of propellant from 0 µÎµ to 24000 µÎµ is realized. Solved the thorny problem of large strain measurement for propellants. In addition, the temperature discrimination measurement in the temperature range of 30 ℃ to 250 ℃ can be realized. Sensor exhibit extremely high stability characteristics and has good compatibility with propellants. The sensor implantation and extraction structure has been designed to improve the survival rate of the sensor inside the solid rocket motors (SRM). Sensors can accurately measure the mechanical and thermal state parameters of propellants, providing effective data support for the health management of SRM.

A biosensing system employing nonlinear dynamic analysis-assisted neural network for drug-induced cardiotoxicity assessment.

Preclinical investigation of drug-induced cardiotoxicity is of importance for drug development. To evaluate such cardiotoxicity, in vitro high-throughput interdigitated electrode-based recording of cardiomyocytes mechanical beating is widely used. To automatically analyze the features from the beating signals for drug-induced cardiotoxicity assessment, artificial neural network analysis is conventionally employed and signals are segmented into cycles and feature points are located in the cycles. However, signal segmentation and location of feature points for different signal shapes require design of specific algorithms. Consequently, this may lower the efficiency of research and the applications of such algorithms in signals with different morphologies are limited. Here, we present a biosensing system that employs nonlinear dynamic analysis-assisted neural network (NDANN) to avoid the signal segmentation process and directly extract features from beating signal time series. By processing beating time series with fixed time duration to avoid the signal segmentation process, this NDANN-based biosensing system can identify drug-induced cardiotoxicity with accuracy over 0.99. The individual drugs were classified with high accuracies over 0.94 and drug-induced cardiotoxicity levels were accurately predicted. We also evaluated the generalization performance of the NDANN-based biosensing system in assessing drug-induced cardiotoxicity through an independent dataset. This system achieved accuracy of 0.85-0.95 for different drug concentrations in identification of drug-induced cardiotoxicity. This result demonstrates that our NDANN-based biosensing system has the capacity of screening newly developed drugs, which is crucial in practical applications. This NDANN-based biosensing system can work as a new screening platform for drug-induced cardiotoxicity and improve the efficiency of bio-signal processing.

Preimplantation genetic testing for a family with usher syndrome through targeted sequencing and haplotype analysis.

BACKGROUND: Preimplantation genetic testing for monogenic defects (PGT-M) has been available in clinical practice. This study aimed to validate the applicability of targeted capture sequencing in developing personalized PGT-M assay. METHODS: One couple at risk of transmitting Usher Syndrome to their offspring was recruited to this study. Customized capture probe targeted at USH2A gene and 350 kb flanking region were designed for PGT-M. Eleven blastocysts were biopsied and amplified by using multiple displacement amplification (MDA) and capture sequencing. A hidden Markov model (HMM) assisted haplotype analysis was performed to deduce embryo's genotype by using single nucleotide polymorphisms (SNPs) identified in each sample. The embryo without paternal rare variant was implanted and validated by conventional prenatal or postnatal diagnostic means. RESULTS: Four embryos were diagnosed as free of father's rare variant, two were transferred and one achieved a successful pregnancy. The fetal genotype was confirmed by Sanger sequencing of fetal genomic DNA obtained by amniocentesis. The PGT-M and prenatal diagnosis results were further confirmed by the molecular diagnosis of the baby's genomic DNA sample. The auditory test showed that the hearing was normal. CONCLUSIONS: Targeted capture sequencing is an effective and convenient strategy to develop customized PGT-M assay.