Reduction in the Sensor Effect on Acoustic Emission Data to Create a Generalizable Library by Data Merging.

The aim of this paper is to discuss the effect of the sensor on the acoustic emission (AE) signature and to develop a methodology to reduce the sensor effect. Pencil leads are broken on PMMA plates at different source-sensor distances, and the resulting waves are detected with different sensors. Several transducers, commonly used for acoustic emission measurements, are compared with regard to their ability to reproduce the characteristic shapes of plate waves. Their consequences for AE descriptors are discussed. Their different responses show why similar test specimens and test conditions can yield disparate results. This sensor effect will furthermore make the classification of different AE sources more difficult. In this context, a specific procedure is proposed to reduce the sensor effect and to propose an efficient selection of descriptors for data merging. Principal Component Analysis has demonstrated that using the Z-score normalized descriptor data in conjunction with the Krustal-Wallis test and identifying the outliers can help reduce the sensor effect. This procedure leads to the selection of a common descriptor set with the same distribution for all sensors. These descriptors can be merged to create a library. This result opens up new outlooks for the generalization of acoustic emission signature libraries. This aspect is a key point for the development of a database for machine learning.

Synthesis, Characterization and Luminescence Sensitivity with Variance in pH, DNA and BSA Binding Studies of Ru(II) Polypyridyl Complexes.

Three ruthenium(II) polypyridyl complexes, [Ru(phen)2(mip)](ClO4)2 (1) (phen =1,10-Phenanthroline), [Ru(bpy)2(mip)](ClO4)2 (2) (bpy = 2,2'bipyridyl) and [Ru(dmb)2(mip)](ClO4)2 (3) (dmb = 4, 4'-dimethyl 2, 2'-bipyridine), were synthesized with an intercalative ligand mip (2-morpholino-1H-imidazo[4,5-f][1, 10]phenanthroline) and characterized by 1H, 13C-NMR, IR, UV-vis, mass spectra and elemental analysis. pH effect, ion selectivity (cations, anions) and solvent sensitivity of complexes were studied. The interaction of these complexes with DNA was performed using absorption, emission spectroscopy and viscosity measurements. The experimental results indicated that the two complexes interacted with calf thymus DNA (CT-DNA) by intercalative mode. BSA (Bovine Serum Albumin) protein binding of these complexes was studied by UV-visible and fluorescence techniques. The binding capacity of these complexes was explained theoretically by molecular docking method.

Luminescent Behavior of Ru(II) Polypyridyl Morpholine Complexes, Synthesis, Characterization, DNA, Protein Binding, Sensor Effect of Ions/Solvents and Docking Studies.

New three ruthenium (II) polypyridyl complexes [Ru(phen)2mpip](2+)(1) {mpip = 2-(4-morpholinophenyl)-1H-imidazo[4,5-f][1,10]phenanthroline}, (phen = 1,10-Phenanthrolene), [Ru(bpy)2mpip](2+)(2) (bpy = 2,2'bipyridyl), [Ru(dmb)2mpip](2+)(3) (dmb = 4, 4-dimethyl 2, 2'-bipyridine) have been synthesized and characterized by spectral studies IR, UV-vis, (1)H, (13)C-NMR, mass and elemental analysis. The binding properties of these three complexes towards calf-thymus DNA (CT-DNA) have been investigated by UV-Vis spectroscopy, different fluorescence methods and viscosity measurements, indicating that all the complexes bind to CT-DNA by means of intercalation, but with different binding affinities. Sensor effect of ions/solvents and BSA (Bovine Serum Albumin) binding studies of these complexes were also studied. Docking studies also reveals that complexes will bind in between base pairs (Intercalate) of DNA and gives information about the binding strength.

Data Merging of AE Sensors with Different Frequency Resolution for the Detection and Identification of Damage in Oxide-Based Ceramic Matrix Composites.

In this paper, acoustic emission data fusion based on multiple measurements is presented for damage detection and identification in oxide-based ceramic matrix composites. Multi-AE (acoustic emission) sensor fusion is considered with the aim of a better identification of damage mechanisms. In this context, tensile tests were conducted on ceramic matrix composites, fabricated with 3M™ Nextel™ 610 fibers and aluminosilicate matrix, with two kinds of AE sensors. Redundant and complementary sensor data were merged to enhance AE system capability and reliability. Data fusion led to consistent signal clustering with an unsupervised procedure. A correlation between these clusters and the damage mechanisms was established thanks to in situ observations. The complementarity of the information from both sensors greatly improves the characterization of sources for their classification. Moreover, this complementarity allows features to be perceived more precisely than using only the information from one kind of sensor.