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Abstract: The paper proposes a novel approach to bring out the potential of complex networks based on graph theory to unwrap the hidden characteristics of cough signals, croup (BC), and pertussis (PS). The spectral and complex network analyses of 48 cough sounds are utilized for understanding the airflow through the infected respiratory tract. Among the different phases of the cough sound time-domain signals of BC and PS – expulsive (X), intermediate (I), and voiced (V) - the phase ‘I’ is noisy in BC due to improper glottal functioning. The spectral analyses reveal high-frequency components in both cough signals with an additional high-intense low-frequency spread in BC. The complex network features created by the correlation mapping approach, like number of edges (E), graph density (G), transitivity (), degree centrality (D), average path length (L), and number of components () distinguishes BC and PS. The higher values of E, G, and for BC indicate its musical nature through the strong correlation between the signal segments and the presence of high-intense low-frequency components in BC, unlike that in PS. The values of D, L, and discriminate BC and PS in terms of the strength of the correlation between the nodes within them. The linear discriminant analysis (LDA) and quadratic support vector machine (QSVM) classifies BC and PS, with greater accuracy of 94.11% for LDA. The proposed work opens up the potentiality of employing complex networks for cough sound analysis, which is vital in the current scenario of COVID-19.
Keywords: Complex network analysis, Auscultation, Croup cough, Pertussis Spectral analysis, Machine learning techniques
Published in RUNG: 30.06.2022; Views: 2565; Downloads: 0
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Abstract: The development of novel digital auscultation techniques has become highly significant in the context of the outburst of the pandemic COVID 19. The present work reports the spectral, nonlinear time series, fractal, and complexity analysis of vesicular (VB) and bronchial (BB) breath signals. The analysis is carried out with 37 breath sound signals. The spectral analysis brings out the signatures of VB and BB through the power spectral density plot and wavelet scalogram. The dynamics of airflow through the respiratory tract during VB and BB are investigated using the nonlinear time series and complexity analyses in terms of the phase portrait, fractal dimension, Hurst exponent, and sample entropy. The higher degree of chaoticity in BB relative to VB is unwrapped through the maximal Lyapunov exponent. The principal component analysis helps in classifying VB and BB sound signals through the feature extraction from the power spectral density data. The method proposed in the present work is simple, cost-effective, and sensitive, with a far-reaching potential of addressing and diagnosing the current issue of COVID 19 through lung auscultation.
Keywords: Breath sound analysis, Fractal dimension, Nonlinear time series analysis, Sample entropy, Hurst exponent, Principal component analysis
Published in RUNG: 28.06.2022; Views: 2435; Downloads: 0
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Abstract: The aim of the present study is to characterize and improve the still insufficient knowledge of the recharge processes that have an important influence on the flow and solute transport in karst aquifers and thus also on the quantity and quality of karst water sources. A binary karst aquifer in the recharge area of the Malenščica and Unica springs, which covers an area of about 820 km2 in SW Slovenia, was selected as the study area. A dense monitoring network was established at 20 observation points (six springs, four ponors, seven water-active caves and three surface streams) for simultaneous monitoring of the hydrological characteristics and the physicochemical properties of the water, the so-called natural tracers. Data-loggers were installed to measure water pressure, temperature and conductivity. During selected storm events, samples were taken for chemical and microbiological analyses and discharge measurements were made. The meteorological and hydrological data of the Slovenian Environment Agency complemented the extensive dataset. Collected data allowed the analysis and comparison of the spatial and temporal variations of the natural tracers under different hydrological conditions. Frequent discharge measurements allowed the generation of rating curves and proved to be a crucial element for understanding the hydraulic processes that determine the functioning of this system. The calculation of the water budget allowed an assessment of the proportion of autogenic and allogenic recharge of the springs and a quantitative estimate of autogenic recharge under different hydrological conditions. The hydrological analysis, i.e. the flow duration curve, the hydrograph separation techniques and the recession analysis, revealed that the Malenščica spring has a higher storage capacity, a greater proportion of autogenic recharge, especially at low-flow, and a slower recession than the Unica spring. This was also confirmed by correlation and spectral analyses, which were also used to investigate the relationships between discharges at ponors and springs. However, the results of the cross-correlation analysis showed hardly any difference between the two springs and in this case proved to be unsuitable for studying the influence of allogenic recharge. Instead, partial cross-correlation analysis was used to control the input parameters of effective precipitation and discharge of one of the sinking streams to determine the contribution of the other sinking stream to the observed spring. The results confirmed differences in allogenic recharge of the Unica and Malenščica springs. Hysteresis analysis has been applied as a complementary method to time series analysis and represents an improved approach to the characterization of the karst hydrological system. The hydraulic approach to the construction of hysteresis enabled a detailed analysis of allogenic and autogenic water interaction and its influence on the Malenščica and Unica springs under different hydrological conditions. Narrow shapes of the hysteresis indicate a direct hydraulic connection between the ponor and the spring and thus a well-developed drainage system. Any deviation towards a convex or concave shape indicates a less developed, more matrix-related drainage system or the influence of other recharge sources. Analysis of physicochemical hysteretic function of individual locations confirmed the differences in the recharge characteristics of the two springs. Compared to the Unica spring, the Malenščica spring has specific recharge characteristics that result in lower vulnerability to the effects of the sinking streams. A greater proportion of autogenic recharge in the initial phase of the storm event is important, as it allows for a time delay of the possible negative effects of the sinking stream. However, possible pollution from the area of autogenic recharge can have strong negative effects, as in this initial phase with low discharges the dilution effect is negligible.
Keywords: karst aquifer, dynamics of natural tracers, storm events, discharge measurements, time series analysis, hysteresis, Unica spring, Malenščica spring
Published in RUNG: 01.03.2022; Views: 3218; Downloads: 122
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Abstract: A unique material, ceria (CeO2), which is widely applied in automobile exhaust catalysts, is functional due to presence of defects in its crystal structure. Furthermore, the structural defects dictate electrical and chemical properties of ceria. The creation of intrinsic oxygen vacancies in ceria is responsible for oxygen-ion conductivity in solid oxide fuel cells. This unfolds the keen interest in ceria defects. Using the analytical technique cathodoluminescence spectroscopy (CLS) we can characterize ceria for its band gap and the defect states within the band gap. Since CLS has a high spatial resolution, high sensitivity to low concentration of defects and ability to obtain depth resolved information it is an obvious technique of choice. The first part of the thesis is an introduction to the topic and description of the experimental techniques. Importance of ceria as a multifaceted material finding applications in areas spanning from energy production and conversion to biomedical applications is detailed. CLS as a tool to understand defect-related optical properties and advancement in the CL detection systems are discussed. To study the relationship between local structure and its impact on CL emission spectra, an X-ray absorption spectroscopy techniques were used. The X-ray absorption near edge structure (XANES) and the Extended x-ray absorption fine structure (EXAFS) techniques are summarized. The second part discusses CL emission from ceria. Initially, CL emission from reduced ceria and its dependence on oxygen vacancy concentration are presented. The origin of emission was attributed to different configurations of the oxygen vacancies and polarons. The recent F center description in ceria was adopted here. The intriguing observation of CL emission quenching as a function of oxygen vacancy concentration was explained on the basis of a relative change in population of F centers in ceria. This demonstrated the relevance of local structure for the CL emission in ceria. In order to have a better understanding of the system, La-doped ceria was proposed as a model system. A precise control over the stoichiometry helped to achieve a desired oxygen vacancy concentration. The CL emission behavior, as observed in reduced ceria, was replicated in the case of La-doped ceria and the analysis revealed that F+ centers favor CL emission whereas F0 centers are disadvantageous. The local structure investigation using EXAFS analysis of both cations Ce and La (K-Edge) showed distortion from the fluorite symmetry and corroborated the F center description of oxygen vacancies in ceria. Our results provide an experimental evidence for F center description involving oxygen vacancies and polarons.
Keywords: ceria, cathodoluminescence spectroscopy, local structure distortion, EXAFS analysis, La doped ceria, luminescence quenching, F centers, dissertations
Published in RUNG: 25.11.2021; Views: 3520; Downloads: 114
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Keywords: neurolinguistics, discourse analysis, language disorders
Published in RUNG: 04.11.2021; Views: 2477; Downloads: 0
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