Damage detection of structures using signal processing and artificial neural networks

Over the last two decades, extensive research has been conducted on structural health monitoring and damage detection in order to reduce the life-cycle cost of structures and improve their reliability and safety. These methods are divided into modal-based and signal-based approaches. Recent advances in the field of sensor technologies have facilitated the use of signal-based methods as practical solution to detect damages in structures. After a sever earthquake, usually there is no possibility for visiting the individual structures. Therefore, application of methods that can detect damage of structures only by using signals recorded at the time of the earthquake is noteworthy. Many existing methods, especially methods based on signal processing are not able to determine the damage severity. This article presents a signal-based seismic structural health monitoring technique for damage detection and evaluating damage severity of a multi-story frame subjected to an earthquake event. As a case study, this article is focused on IASC–ASCE benchmark problem to provide possibility for side-by-side comparison. First three signal processing techniques including EMD, HVD and LMD, which are categorized as instantaneous time-frequency methods, have been compared to find a method with the best resolution in extracting frequency responses. Based on the results EMD has proved to outperform than the others. Second, EMD is used to extract the acceleration response of the sensors. Results show that by taking advantage of signal processing and artificial intelligence techniques in this research, damage detection of structures was carried out for three levels including damage occurrence, damage severity and location of the damage

6-Methoxy Podophyllotoxin Induces Apoptosis via Inhibition of TUBB3 and TOPIIA Gene Expressions in 5637 and K562 Cancer Cell Lines

Objective Podophyllotoxin (PTOX), a natural compound in numerous plants, contains remarkable biological properties that include anti-tumor, anti-viral such as anti-human im- munodeficiency virus (HIV) activities. In order to avoid its adverse effects, various com- pounds have been derived from PTOX. 6-methoxy PTOX (MPTOX) is one of the natural PTOX derivatives with an extra methoxy group. MPTOX is mostly isolated from the Linum species. This study has sought to determine the biological effects of MPTOX on cancer cell lines, 5637 and K562. Materials and Methods In this experimental study, we treated the 5637 and K562 cancer cell lines with MPTOX in a doseand time-dependent manner. Apoptosis was examined by flow cytometry and viability rate was analyzed by the MTT assay. Expressions of the tubulin (TUBB3) and topoisomerase II (TOPIIA) genes were determined by real-time poly- merase chain reaction (PCR). Results Treatment with MPTOX led to significant induction of apoptosis in cancer cells compared to control cells. Gene expression analysis showed reduced levels of TUBB3 and TOPIIA mRNA following MPTOX treatment. Conclusion MPTOX inhibited TUBB3 and TOPIIA gene expression and subsequently induced cell death through apoptosis. These results suggested that MPTOX could be considered a potential anti-tumor agent

The Effects of Melatonin in Patients with Nonalcoholic Fatty Liver Disease: A Randomized Controlled Trial

Background: This study was designed to evaluate the effect of melatonin on nonalcoholic fatty liver disease (NAFLD) in compared to placebo. Materials and Methods: A total of 100 patients with histopathological diagnosis NAFLD in two groups of case and control received oral melatonin or placebo thrice daily for 3 months. Collected data were weight, waist, systolic blood pressure (SBP), diastolic blood pressure (DBP), alanine aminotransferase (ALT), aspartate aminotransferase (AST), high sensitive C-reactive protein (hsCRP), fatty liver grade, and side effects which were measured at baseline and after treatment period using standard clinical chemistry techniques. Results: Before treatment the mean of weight, waist, SBP, DBP, ALT, AST, and hsCRP between cases and controls were similar (P > 0.5). After treatment, only the differences in the mean of hsCRP in cases was significantly lower than controls (P = 0.003). In case group, all variables after treatment were significantly decreased compare to baseline (P > 0.5) and only AST after treatment was similar to before treatment (P > 0.5). The mean of a decrease in the level of weight, waist, SBP, and ALT were not statistically significant between groups (P > 0.5). In the case group in compare to control group the level of DBP, AST, and hsCRP significantly more decreased. After treatment fatty, liver grade was statistically improved in more cases than controls (P = 0.001). Side effects were similar between the two groups. Conclusion: Melatonin significantly decreases liver enzymes, so the use of melatonin in patients with NAFLD can be effective

Single cell classification using statistical learning on mechanical properties measured by mems tweezers

International audienceCell population is heterogenous and so presents a wide range of properties as metastatic potential. But using rare cells for clinical applications requires precise classification of individual cells. Here, we propose a multi-parameter analysis of single cells to classify them using statistical learning techniques and to predict the sub-population of each cell, although they may have close characteristics. We used MEMS tweezers to analyze mechanical properties (stiffness, viscosity, and size) of single cells from two different breast cancer cell lines in a controlled environment and run supervised learning methods to predict the population they belong to. This label-free method is a significant step forward to distinguish rare cell sub-populations for clinical applications

Pairing cells of different sizes in a microfluidic device for immunological synapse monitoring

International audienceAnalyzing cell–cell interaction is essential to investigate how immune cells function. Elegant designs have been demonstrated to study lymphocytes and their interaction partners. However, these devices have been targeting cells of similar dimensions. T lymphocytes are smaller, more deformable, and more sensitive to pressure than many cells. This work aims to fill the gap of a method for pairing cells with different dimensions. The developed method uses hydrodynamic flow focusing in the z-direction for on-site modulation of effective channel height to capture smaller cells as single cells. Due to immune cells' sensitivity to pressure, the proposed method provides a stable system without any change in flow conditions at the analysis area throughout experiments. Paired live cells have their activities analyzed with calcium imaging at the immunological synapse formed under a controlled environment. The method is demonstrated with primary human T lymphocytes, acute myeloid leukemia (AML) cell lines, and primary AML blasts