Otoacoustic Emissions

Acoustic emission (AE) is a phenomenon in which elastic or stress waves are emitted from rapid, localized change of strain energy in material. The practical application of the AE first emerged in the 1950's, but only in the last 20 years the science, technology and applications of AE have progressed significantly. Currently AE has become one of the most important non-destructive testing techniques. This interdisciplinary book consists of nine chapters, which is a proof of the fact that the AE method is continuously and intensively developing and widely applied in: on-line monitoring of civil-engineering structures (e.g. highway bridges, skyscrapers, dams etc.), fatigue cracks detection and location in pressure vessels and pipelines, damage assessment in fibre-reinforced polymer-matrix composites, monitoring welding applications and corrosion processes, bearing condition diagnostics, partial discharge sources detection and location in power transformers and generators, monitoring the drying process of materials, quality evaluation of fruits and vegetables and in otoacoustic emission analysis

Electronic Journal of Theoretical Physics Non Linear Assessment of Musical Consonance

Abstract: The position of intervals and the degree of musical consonance can be objectively explained by temporal series formed by mixing two pure sounds covering an octave. This result is achieved by means of Recurrence Quantification Analysis (RQA) without considering neither overtones nor physiological hypotheses. The obtained prediction of a consonance can be considered a novel solution to Galileo’s conjecture on the nature of consonance. It constitutes an objective link between musical performance and listeners ’ hearing activity

Automatic Detection of Aerobic Threshold through Recurrence Quantification Analysis of Heart Rate Time Series

During exercise with increasing intensity, the human body transforms energy with mechanisms dependent upon actual requirements. Three phases of the body’s energy utilization are recognized, characterized by different metabolic processes, and separated by two threshold points, called aerobic (AerT) and anaerobic threshold (AnT). These thresholds occur at determined values of exercise intensity(workload) and can change among individuals. They are considered indicators of exercise capacities and are useful in the personalization of physical activity plans. They are usually detected by ventilatory or metabolic variables and require expensive equipment and invasive measurements. Recently, particular attention has focused on AerT, which is a parameter especially useful in the overweight and obese population to determine the best amount of exercise intensity for weight loss and increasing physical fitness. The aim of study is to propose a new procedure to automatically identify AerT using the analysis of recurrences (RQA) relying only on Heart rate time series, acquired from a cohort of young athletes during a sub-maximal incremental exercise test (Cardiopulmonary Exercise Test, CPET) on a cycle ergometer. We found that the minima of determinism, an RQA feature calculated from the Recurrence Quantification by Epochs (RQE) approach, identify the time points where generic metabolic transitions occur. Among these transitions, a criterion based on the maximum convexity of the determinism minima allows to detect the first metabolic threshold. The ordinary least products regression analysis shows that values of the oxygen consumption VO2 , heart rate (HR), and Workload correspondent to the AerT estimated by RQA are strongly correlated with the one estimated by CPET (r > 0.64). Mean percentage differences are <2% for both HR and VO2 and <11% for Workload. The Technical Error for HR at AerT is <8%; intraclass correlation coefficients values are moderate (≥0.66) for all variables at AerT. This system thus represents a useful method to detect AerT relying only on heart rate time series, and once validated for different activities, in future, can be easily implemented in applications acquiring data from portable heart rate monitors

Physical Education on the Beach: An Alternative Way to Improve Primary School Children’s Skill- and Health-Related Outcomes during the COVID-19 Pandemic

: The COVID-19 restrictions could preclude children from participating in physical education (PE) interventions. This study aimed to evaluate the efficacy of a PE intervention conducted on the beach on children's skill- and health-related outcomes, as a possible alternative PE intervention that could be also applied during the COVID-19 pandemic. The study involved 106 primary school children, randomly assigned to the traditional indoor (TI) intervention or to the experimental outdoor (EO) intervention. The intervention period lasted 4 months and consisted of two 1-h sessions per week. Intervention was conducted just before the beginning of the COVID-19 pandemic. Children's anthropometric parameters (height, weight, BMI, body fat percentage, and abdominal circumference), fitness parameter (VO2peak), health parameters (resting heart rate, and systolic and diastolic blood pressure), gross motor coordination, and physical activity level were assessed before and after intervention. Both groups significantly improved fitness and motor coordination but worsened some anthropometric parameters (weight, abdominal circumference) after the intervention period. The EO group showed a higher increase of gross motor coordination than the TI group. Results of this study demonstrated that children benefited from a well-structured PE intervention conducted in the natural environment of the beach improving physical fitness and gross motor coordination. Therefore, planning outdoor PE interventions could be an alternative and safe way to encourage and implement physical activity at school during the particular period of COVID-19 pandemic

RQA correlations on business cycles: A comparison between real and simulated data

Business cycles are complex phenomena which oscillate because of economic downturns and expansions. Recurrence quantification analysis (RQA) detects state changes without necessitating any a priori mathematical assumption and highlight hidden features of the dynamics both at equilibrium and near transition phases. This paper aims to explore some potential application of recurrence quantification analysis in detecting cycles in economy and compares them with oscillations derived from a Kaldor-Kalecki non-linear model