Vibration Analysis for NDE of Ceramic Components

In this contribution we study vibration testing for ceramic parts on the example of an electrolyte cup, used in a prospective power cells design. An adapted experimental arrangement for the vibration excitation and the acoustic measurements was built and tested. In parallel, extensive numerical modal analysis simulations were performed using ANSYS. The resonance spectra obtained by modelling agree with the experimentally determined spectra in such a way that the experimentally determined eigenfrequencies can be assigned to the cup modes. The correctness of this identification was verified by direct mode visualization with scanning laser doppler vibrometry. A much faster and potentially in-line capable method for experimental mode identification is the simultaneous measurement at several points using a microphone array and subsequent signal evaluation with operational modal analysis. This procedure was successfully tested. Features in the spectra connected with the presence of flaws are discussed. These features include the drop of some eigenfrequencies and the splitting of degenerated modes.

Multichannel Heterodyne Spectroradiometer for Atmospheric Greenhouse Gas Measurements

<p>We present a portable, multichannel laser heterodyne spectroradiometer (MLHS) with a spectral resolution of 0.0013 cm-1 for precision column measurements and vertical profiling of atmospheric greenhouse gases (GHG). Sample spectra of CO<sub>2</sub> and CH<sub>4</sub> absorption lines obtained by direct Sun observations have allowed us to measure GHG column abundance with a precision of 0.5% for CO<sub>2</sub> and 10% for CH<sub>4</sub>, as well as to retrieve their vertical profiles and to get a vertical profile of the stratospheric wind Rodin et al. (2020). The fundamentals and specifics of the multichannel configuration implementation of heterodyne receivers are presented in Zenevich et al. (2020). This work presents the first data of atmospheric CO<sub>2</sub> and CH<sub>4</sub> measurements, which were taken in a 4-channel configuration of the heterodyne receiver. Such configuration has allowed us to get atmospheric spectra with the SNR 300-500 within 2 minutes period of signal integration and keep the high spectral resolution. The results of retrieving CO<sub>2</sub> and CH<sub>4</sub> vertical concentration profiles and vertical profiles of the stratospheric wind are also presented.</p><p> </p><p><strong>Acknowledgments</strong></p><p>This work has been supported by the Russian Foundation for Basic Research grants # 19-29-06104  (A.V. Rodin, M. V. Spiridonov, I.Sh. Gazizov) and # 19-32-90276 (S. G. Zenevich).</p><p> </p><p><strong>References:</strong></p><p>Zenevich S. et al.: The improvement of dark signal evaluation and signal-to-noise ratio of multichannel receivers in NIR heterodyne spectroscopy application for simultaneous CO2 and CH4 atmospheric measurements, OSA Continuum, 3, 7, 1801-1810, doi:10.1364/OSAC.395094, 2020.</p><p>Rodin, A. et al.: Vertical wind profiling from the troposphere to the lower mesosphere based on high-resolution heterodyne near-infrared spectroradiometry, Atmos. Meas. Tech., 13, 2299–2308, doi:10.5194/amt-13-2299-2020, 2020.</p>

CLASSIFICATION OF BRAIN SIGNALS FOR RPAS CONTROL IN THE TREATMENT OF ATTENTION DEFICIT HYPERACTIVITY DISORDER

The Attention Deficit Hyperactivity Disorder (ADHD) is characterized by a difficulty in processing feedback regarding the current state of the concentration of an individual. One of the main lines of research in the treatment of ADHD involved the employment of electroencephalography (EEG) Neurofeedback as a means of providing a quantification and representation of the concentration level. The current investigation constitutes a first step in developing an application of Remotely Piloted Aircraft Systems aiding in the treatment of ADHD employing a Brain Computer Interface, based on the measurements detected by an EEG sensor. These measurements modify the flight height of a quadrotor according to the signal evaluation. In order to develop the proposed system, a real-time mechanism for processing and classifying the electrophysiological artifacts has been developed. Finally, the processed signals are then fed into the aircraft controller, modifying the aircraft flight and thus providing the desired feedback to the user. Keywords: BCI; drone; RPAS; EEG; ADHD; Neurofeedback; machine learning; neural network.

A Confidence Habitats Methodology in MR Quantitative Diffusion for the Classification of Neuroblastic Tumors

Background/Aim: In recent years, the apparent diffusion coefficient (ADC) has been used in many oncology applications as a surrogate marker of tumor cellularity and aggressiveness, although several factors may introduce bias when calculating this coefficient. The goal of this study was to develop a novel methodology (Fit-Cluster-Fit) based on confidence habitats that could be applied to quantitative diffusion-weighted magnetic resonance images (DWIs) to enhance the power of ADC values to discriminate between benign and malignant neuroblastic tumor profiles in children. Methods: Histogram analysis and clustering-based algorithms were applied to DWIs from 33 patients to perform tumor voxel discrimination into two classes. Voxel uncertainties were quantified and incorporated to obtain a more reproducible and meaningful estimate of ADC values within a tumor habitat. Computational experiments were performed by smearing the ADC values in order to obtain confidence maps that help identify and remove noise from low-quality voxels within high-signal clustered regions. The proposed Fit-Cluster-Fit methodology was compared with two other methods: conventional voxel-based and a cluster-based strategy. Results: The cluster-based and Fit-Cluster-Fit models successfully differentiated benign and malignant neuroblastic tumor profiles when using values from the lower ADC habitat. In particular, the best sensitivity (91%) and specificity (89%) of all the combinations and methods explored was achieved by removing uncertainties at a 70% confidence threshold, improving standard voxel-based sensitivity and negative predictive values by 4% and 10%, respectively. Conclusions: The Fit-Cluster-Fit method improves the performance of imaging biomarkers in classifying pediatric solid tumor cancers and it can probably be adapted to dynamic signal evaluation for any tumor.

Integrating Regulatory Drug Label Information to Facilitate Evaluation of Adverse Events in Pharmacovigilance

Background: Efficiency and accuracy for signal detection and evaluation activities are integral components of routine Pharmacovigilance (PV) practices. However, an Individual Case Safety Report (ICSR) may consist of a variety of confounders such as Concomitant Medications (CM), Past Medical History (PMH), and concurrent medical conditions that influence a safety officer’s evaluation of a potential Adverse Event (AE). Limited pharmacovigilance systems are currently available as a tool designed to enhance the efficiency and accuracy of signal detection and management. Objective: To introduce a systemic approach to make critical safety information readily available for users in order to discern possible interferences from CM and make informed decisions on the signal evaluation process – saving time while improving quality. Methods: Oracle Empirica Signal software was utilized to extract cases with CM that are Known Implicating Medications (KIM) for each AE according to public regulatory information from drug labels – FDA Structured Product Labeling (SPL) or EMA Summary of Product Characteristics (SPC). SAS Enterprise Guide was used to further process the data generated from Oracle Empirica Signal software. Results: For any target drug being evaluated for safety purposes, a KIM reference table can be generated, which summarizes all potential causality contributions from CMs. Conclusion: In addition to providing standalone KIM table as reference, adoption of this concept and automation may also be fully integrated into commercial signal detection and management software packages for easy use and accessibility and may even lead to reduced False Positive rate in signal detection within the PV space.