Search results for "damage [radiation]"
showing 10 items of 101 documents
Parvovirus B19 nonstructural protein-induced damage of cellular DNA and resultant apoptosis.
2010
Parvovirus B19 is a widespread virus with diverse clinical presentations. The viral nonstructural protein, NS1, binds to and cleaves the viral genome, and induces apoptosis when transfected into nonpermissive cells, such as hepatocytes. We hypothesized that the cytotoxicity of NS1 in such cells results from chromosomal DNA damage caused by the DNA-nicking and DNA-attaching activities of NS1. Upon testing this hypothesis, we found that NS1 covalently binds to cellular DNA and is modified by PARP, an enzyme involved in repairing single-stranded DNA nicks. We furthermore discovered that the DNA nick repair pathway initiated by poly(ADPribose)polymerase and the DNA repair pathways initiated by …
EGFP Reporters for Direct and Sensitive Detection of Mutagenic Bypass of DNA Lesions
2020
The sustainment of replication and transcription of damaged DNA is essential for cell survival under genotoxic stress
In Vitro Assessment of the Genotoxic Hazard of Novel Hydroxamic Acid- and Benzamide-Type Histone Deacetylase Inhibitors (HDACi)
2020
Histone deacetylase inhibitors (HDACi) are already approved for the therapy of leukemias. Since they are also emerging candidate compounds for the treatment of non-malignant diseases, HDACi with a wide therapeutic window and low hazard potential are desirable. Here, we investigated a panel of 12 novel hydroxamic acid- and benzamide-type HDACi employing non-malignant V79 hamster cells as toxicology guideline-conform in vitro model. HDACi causing a &ge
Damage identification by a modified Ant Colony Optimization for not well spaced frequency systems
2011
Recently, it has been shown , that a damage detection strategy based on a proper functional calculated on the analytical signal of the structural dynamical response, consents to identify very low damage level. In this regard, they stressed the efficiency of Hilbert Transform to obtain the analytical response representation that shows more sensitivity for predicting damage with respect to the simple signal response. Then, a damage identification procedure based on the minimization of the difference between theoretical and measured data was proposed with satisfactory results. Unfortunately, this procedure, since the need of use of band pass filter around the natural frequency of the system, f…
Towards Low-Cost Pavement Condition Health Monitoring and Analysis Using Deep Learning
2020
Governments are faced with countless challenges to maintain conditions of road networks. This is due to financial and physical resource deficiencies of road authorities. Therefore, low-cost automated systems are sought after to alleviate these issues and deliver adequate road conditions for citizens. There have been several attempts at creating such systems and integrating them within Pavement management systems. This paper utilizes replicable deep learning techniques to carry out hotspot analyses on urban road networks highlighting important pavement distress types and associated severities. Following this, analyses were performed illustrating how the hotspot analysis can be carried out to…
Condition Monitoring Technologies for Synthetic Fiber Ropes - a Review
2020
This paper presents a review of different condition monitoring technologies for fiber ropes. Specifically, it presents an overview of the articles and patents on the subject, ranging from the early 70’s up until today with the state of the art. Experimental results are also included and discussed in a conditionmonitoring context,where failuremechanisms and changes in physical parameters give improved insight into the degradation process of fiber ropes. From this review, it is found that automatic width measurement has received surprisingly little attention, and might be a future direction for the development of a continuous condition monitoring system for synthetic fiber ropes.
Machine learning at the interface of structural health monitoring and non-destructive evaluation
2020
While both non-destructive evaluation (NDE) and structural health monitoring (SHM) share the objective of damage detection and identification in structures, they are distinct in many respects. This paper will discuss the differences and commonalities and consider ultrasonic/guided-wave inspection as a technology at the interface of the two methodologies. It will discuss how data-based/machine learning analysis provides a powerful approach to ultrasonic NDE/SHM in terms of the available algorithms, and more generally, how different techniques can accommodate the very substantial quantities of data that are provided by modern monitoring campaigns. Several machine learning methods will be illu…
A Boundary Element Formulation for Modelling Structural Health Monitoring Applications
2015
In this paper, a boundary element formulation for modelling pitch-catch damage detection applications is introduced. The current formulation has been validated by both finite element analyses and physical experiments. Comparing to the widely used finite element method, the current formulation does not only use less computational resources, but also demonstrates higher numerical stability. doi: 10.12783/SHM2015/221
Modal Analysis of a Reinforced Concrete Frame in Various States of Damage
2005
The purpose of this paper is to report selected results of an experiment in which two, natural size r/c frames were put on shaking table and subjected to a sequence of seismic excitations with increasing intensity interlaced with low level, diagnostic tests. The shaking table experiment aimed at working out new methodology for monitoring vibrations of r/c structures to assess their state. Characteristic decrease of natural frequencies and increase of structural damping was observed and analyzed in detail. It was interesting to note 20 per cent drop in natural frequencies prior to visual detection of any cracks.
An unsupervised Learning Algorithm for Fatigue Crack Detection in Waveguides
2009
Ultrasonic guided waves (UGWs) are a useful tool in structural health monitoring (SHM) applications that can benefit from built-in transduction, moderately large inspection ranges, and high sensitivity to small flaws. This paper describes an SHM method based on UGWs and outlier analysis devoted to the detection and quantification of fatigue cracks in structural waveguides. The method combines the advantages of UGWs with the outcomes of the discrete wavelet transform (DWT) to extract defect-sensitive features aimed at performing a multivariate diagnosis of damage. In particular, the DWT is exploited to generate a set of relevant wavelet coefficients to construct a uni-dimensional or multi-di…