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2. Wavelength-resolved reverberation mapping of quasar CTS C30.10: Dissecting Mg II and Fe II emission regionsRaj Prince, Michal Zajaček, Bożena Czerny, Piotr Trzcionkowski, Mateusz Bronikowski, Catalina Sobrino Figaredo, Swayamtrupta Panda, Mary Loli Martinez-Aldama, Krzysztof Hryniewicz, Vikram Kumar Jaiswal, Marzena Śniegowska, Mohammad-Hassan Naddaf, Maciej Bilicki, Martin Haas, Marek Jacek Sarna, Vladimir Karas, Aleksandra Olejak, Robert Przyłuski, Mateusz Rałowski, Andrzej Udalski, Ramotholo R. Sefako, Anja Genade, Hannah L. Worters, 2022, original scientific article Abstract: Context. We present the results of the reverberation monitoring of the Mg II broad line and Fe II pseudocontinuum for the luminous quasar CTS C30.10 (z = 0.90052) with the Southern African Large Telescope in 2012–2021.
Aims. We aimed at disentangling the Mg II and UV Fe II variability and the first measurement of UV Fe II time delay for a distant quasar.
Methods. We used several methods for the time-delay measurements and determined the Fe II and Mg II time delays. We also performed a wavelength-resolved time delay study for a combination of Mg II and Fe II in the 2700–2900 Å rest-frame wavelength range.
Results. We obtain a time delay for Mg II of 275.5−19.5+12.4 days in the rest frame, and we have two possible solutions of 270.0−25.3+13.8 days and 180.3−30.0+26.6 in the rest frame for Fe II. Combining this result with the old measurement of Fe II UV time delay for NGC 5548, we discuss for first time the radius-luminosity relation for UV Fe II with the slope consistent with 0.5 within the uncertainties.
Conclusions. Because the Fe II time delay has a shorter time-delay component but the lines are narrower than Mg II, we propose that the line-delay measurement is biased toward the part of the broad line region (BLR) facing the observer. The bulk of the Fe II emission may arise from the more distant BLR region, however, the region that is shielded from the observer.
Keywords: accretion, accretion disks / quasars: emission lines / quasars: individual: CTS C30.10 / techniques: spectroscopic / techniques: photometric
Published in RUNG: 13.11.2023; Views: 603; Downloads: 3
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3. Tailoring the thermal diffusivity of polyvinylidene fluoride via carbon source integration : a photothermal beam deflection studyMohanachandran Nair Sindhu Swapna, Dorota Korte, Sankaranarayana Iyer Sankararaman, 2023, original scientific article Keywords: cellulose, camphor soot, lignin, PVDF, photothermal techniques, beam deflection, hydroxyl groups
Published in RUNG: 21.08.2023; Views: 792; Downloads: 6
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5. Infrared spectra in amorphous alumina : a combined ab initio and experimental studyLuigi Giacomazzi, Nikita S. Shcheblanov, Mikhail E. Povarnitsyn, Yanbo Li, Andraž Mavrič, Barbara Zupančič, Jože Grdadolnik, Alfredo Pasquarello, 2023, original scientific article Abstract: We present a combined study based on the experimental measurements of an infrared (IR) dielectric function and first-principles calculations of IR spectra and the vibrational density of states (VDOS) of amorphous alumina (am−Al2O3). In particular, we show that the main features of the imaginary part of the dielectric function ε2(ω) at ∼380 and 630 cm−1 are related to the motions of threefold-coordinated oxygen atoms, which are the vast majority of oxygen atoms in am-Al2O3. Our analysis provides an alternative point of view with respect to an earlier suggested assignment of the vibrational modes, which relates them to the stretching and bending vibrational modes of AlOn (n=4, 5, and 6) polyhedra. Our assignment is based on the additive decomposition of the VDOS and ε2(ω) spectra, which shows that (i) the band at ∼380cm−1 features oxygen motions occurring in a direction normal to the plane defined by the three nearest-neighbor aluminum atoms, i.e., out-of-plane motions of oxygen atoms; (ii) Al-O stretching vibrations (i.e., in-plane motions of oxygen atoms) appear at frequencies above ∼500cm−1, which characterize the vibrational modes underlying the band at ∼630cm−1. Aluminum and fourfold-coordinated oxygen atoms contribute uniformly to the VDOS and ε2(ω) spectra in the frequency region ∼350–650 cm−1 without causing specific features. Our numerical results are in good agreement with the previous and presently obtained experimental data on the IR dielectric function of am−Al2O3 films. Finally, we show that the IR spectrum can be modeled successfully by assuming isotropic Born charges for aluminum atoms and fourfold-coordinated oxygen atoms, while requiring the use of three parameters, defined in a local reference frame, for the anisotropic Born charges of threefold-coordinated oxygen atoms.
Keywords: dielectric properties, microstructure, amorphous materials, density functional calculations, infrared techniques, aluminium oxide
Published in RUNG: 10.05.2023; Views: 1182; Downloads: 7
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6. Improved photopyroelectric (PPE) configuration for thermal effusivity investigations of porous solidsCarmen Tripon, Mohanachandran Nair Sindhu Swapna, Nicoleta Cobirzan, Dorota Korte, Robert Gutt, Marcel Bojan, Mladen Franko, Dorin Dadarlat, 2023, original scientific article Keywords: photothermal techniques, photopyroelectric calorimetry, thermal effusivity, porous solids, building materials
Published in RUNG: 12.04.2023; Views: 1079; Downloads: 23
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7. Neural net pattern recognition based auscultation of croup cough and pertussis using phase portrait featuresMohanachandran Nair Sindhu Swapna, 2021, original scientific article Abstract: Cough signal analysis for understanding the pathological condition has become important from the outset of the exigency posed by the epidemic COVID-19. The present work suggests a surrogate approach for the classification of cough signals - croup cough (CC) and pertussis (PT) – based on spectral, fractal, and nonlinear time-series techniques. The spectral analysis of CC reveals the presence of more frequency components in the short duration cough sound compared to PT. The musical nature of CC is unveiled not only through the spectral analysis but also through the phase portrait features – sample entropy (S), maximal Lyapunov exponent (L), and Hurst exponent (Hb). The modifications in the internal morphology of the respiratory tract, giving rise to more frequency components associated with the complex airflow dynamics, get staged through the higher fractal dimension of CC. Among the two supervised classification tools, cubic KNN (CKNN) and neural net pattern recognition (NNPR), used for classifying the CC and PT signals based on nonlinear time series parameters, NNPR is found better. Thus, the study opens the possibility of identification of pulmonary pathological conditions through cough sound signal analysis.
Keywords: Croup cough
Pertussis
Fractal dimension
Phase portrait
Sample entropy
Machine learning techniques
Published in RUNG: 04.07.2022; Views: 999; Downloads: 0
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8. Fractal and time-series analyses based rhonchi and bronchial auscultation: A machine learning approachMohanachandran Nair Sindhu Swapna, 2022, original scientific article Abstract: Objectives: The present work reports the study of 34 rhonchi (RB) and
Bronchial Breath (BB) signals employing machine learning techniques, timefrequency, fractal, and non-linear time-series analyses. Methods: The timefrequency analyses and the complexity in the dynamics of airflow in BB
and RB are studied using both Power Spectral Density (PSD) features and
non-linear measures. For accurate prediction of these signals, PSD and nonlinear measures are fed as input attributes to various machine learning
models. Findings: The spectral analyses reveal fewer, low-intensity frequency
components along with its overtones in the intermittent and rapidly damping
RB signal. The complexity in the dynamics of airflow in BB and RB is investigated
through the fractal dimension, Hurst exponent, phase portrait, maximal
Lyapunov exponent, and sample entropy values. The greater value of entropy
for the RB signal provides an insight into the internal morphology of the airways
containing mucous and other obstructions. The Principal Component Analysis
(PCA) employs PSD features, and Linear Discriminant Analysis (LDA) along
with Pattern Recognition Neural Network (PRNN) uses non-linear measures
for predicting BB and RB. Signal classification based on phase portrait
features evaluates the multidimensional aspects of signal intensities, whereas
that based on PSD features considers mere signal intensities. The principal
components in PCA cover about 86.5% of the overall variance of the data class,
successfully distinguishing BB and RB signals. LDA and PRNN that use nonlinear time-series parameters identify and predict RB and BB signals with 100%
accuracy, sensitivity, specificity, and precision. Novelty: The study divulges the
potential of non-linear measures and PSD features in classifying these signals
enabling its application to be extended for low-cost, non-invasive COVID-19
detection and real-time health monitoring.
Keywords: lung signal, fractal analysis, sample entropy, nonlinear timeseries, machine learning techniques
Published in RUNG: 30.06.2022; Views: 1282; Downloads: 0
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9. Complex network-based cough signal analysis for digital auscultation: a machine learning approachMohanachandran Nair Sindhu Swapna, 2022, original scientific article 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: 1310; Downloads: 0
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10. Towards a novel method for iron species determination in Antarctic sea iceHanna Budasheva, Arne Bratkič, Dorota Korte, Mladen Franko, 2021, published scientific conference contribution abstract Abstract: Sea-ice borne iron has been found to be an important factor controlling Southern Ocean phytoplankton growth [1]. Knowing the amount and chemical speciation of its labile fraction in sea ice would advance our understanding of the involved processes. Unfortunately, it is rather difficult to perform their measurement because of limited access to the Antarctic. Thus there is a strong need for the development of a quick, simple and reliable technique for determination of iron and its speciation in sea-ice that ensures also low enough limits of detection. Recently, diffusive gradients in thin films (DGT) have been widely used as passive samplers for collecting time-averaged data on the concentrations of transition metals in different media [2]. DGTs are further coupled to an analytical technique that in case of detecting metals in passive sampler films primarily requires their extraction [3], which may potentially lead to changes of the metal specification. In the present study, the beam deflection spectrometry (BDS) is coupled to DGT and used to determine the average concentration of iron in the sea ice samples collected at the Davis Station in the Antarctic. Such a combined technique has been already successfully applied for detecting labile iron species in freshwater sediments [4]. The obtained BDS data were validated by thermal lens spectrometry (TLS) and UV-Vis spectrophotometry (SPEC). The distribution of iron species over a given ice surface area using the DGT-BDS technique revealed total iron concentrations in the range of 0.6 – 5.3 μgL-1, whereas the Fe2+ content was found to be in the range of 0.1 – 1.5 μgL-1. The range taking into account all of the measurement points (5×4), the precision of a single measured point is 0.2 μgL-1. The calculated 24 h-average concentration of total Fe labile species in the ice by using BDS is 2.3 ± 0.5 μgL-1, which coincides with data obtained by SPEC (2.5 ± 0.4 μgL-1) and TLS (2.39 ± 0.02 μgL-1). Our results indicate that it is possible to develop a robust, contamination-resilient detection method for measuring the labile iron species concentration in the sea ice. In opposite to TLS and SPEC, BDS-DGT provides reliable information not only about the speciation of iron but also about their distribution on the ice surface.
Keywords: beam deflection spectrometry, diffusive gradients, thin films, iron species, photothermal techniques, Antarctic sea ice
Published in RUNG: 30.11.2021; Views: 2222; Downloads: 0
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