1251. Study of Drug Diffusion rate by beam deflection techniqueMohanachandran Nair Sindhu Swapna, 2017, original scientific article Abstract: Drug administration is an unavoidable part of treatment. When a drug is administered orally or intravenously, it gets absorbed into the blood stream. The rate and efficiency of absorption depend on the route of
administration. When a drug is administered through the oral route, it penetrates the epithelial cells of the intestinal mucosa. The diffusion of the drug into the blood stream depends on various parameters, such as concentration, temperature, and the nature of the mucous membrane. The passive diffusion of drugs is found to obey
Fick’s law. Water soluble drugs penetrate the cell membrane through aqueous channel or pores. Hence, the
study of diffusion of drugs into the water and finally into the blood stream is important. An attempt has been made
to study the diffusion of the drug in water as 60% to 80% of human body is water. For the study of drug diffusion in
water, a commonly used cough syrup of specific gravity 1.263 is used. It is found that the diffusion rate increases
with the concentration of the drug.
Keywords: laser beam deflection, diffusion coefficient, Fick’s law, sodium chloride, syrup
Published in RUNG: 30.06.2022; Views: 1203; Downloads: 0
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1252. Fractal and fingerprint analysis through phase embedded diffraction patternMohanachandran Nair Sindhu Swapna, 2017, original scientific article Abstract: Fingerprint recognition is the most popular biometric identification method currently employed
in security applications. Though there are several optical methods for fingerprint analysis based on
intensity recording, phase recording alone can give the precise result. Interference and diffraction
phenomenon are capable of recording phase variations. In the present method diffraction patterns
corresponding to the fingerprints are generated and the spacing between the ridges is calculated. The
spacing between ridges is found to be in agreement with the value measured using the software ImageJ.
The fingerprint impressions of more than thirty-five persons are recorded and analyzed using the
statistical tools in Matlab.The fingerprints are also subjected to fractal analysis. The program could
successfully identify a fingerprint from the database. The present work is the first report of fingerprint
analysis from diffraction pattern
Keywords: Diffraction, Skew, Kurtosis, Fractals
Published in RUNG: 30.06.2022; Views: 1105; Downloads: 0
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1253. Carbon Nanonecklaces with Carbon Nanotubes and Carbon DotsMohanachandran Nair Sindhu Swapna, Sankararaman S, 2017, original scientific article Abstract: Carbon nanoparticles (CNP) have gained significant attention representing
unique carbon-based nanomaterials that find applications in various fields of
science and technology. Carbon nanotubes (CNTs) and carbon dots (CDs)
have now been widely employed as an electrode in super capacitors, as
fluorescent nanomaterials for imaging and for fuel cell applications. In the
present work, we describe a simple, low cost and chemical free method of
synthesizing stable CNPs aligned in the form of a chain popularly known as
carbon necklace with CNTs and CDs. Carbon nanoparticles are synthesized by
controlled combustion of camphor in a single step flame process. The CNPs
synthesized are characterized using X-ray Powder diffraction (XRD), Raman
Spectroscopy, Energy Dispersive X ray diffraction (EDX), Fourier Transform
Infrared Spectroscopy (FTIR), UV-Visible absorption and Photoluminescent
(PL) Spectroscopy. The morphology and size of the CNPs are examined using
Field Emission Scanning Electron Microscope (FESEM) which shows
‘necklace’ structure. The CNPs are collected at two different heights and the
particles formed are found in the range 30 to 60 nm. The UV- Visible and PL
Spectra of the CNPs obtained show the presence CDs. The Raman
Spectroscopic and XRD analysis indicate the presence of CNTs in the sample.
Keywords: Carbon nanoparticles, Combustion, Carbon nanotubes, Carbon
dots, Carbon necklaces
Published in RUNG: 30.06.2022; Views: 1264; Downloads: 0
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1254. Investigation of graphene oxide in diesel sootMohanachandran Nair Sindhu Swapna, Sankararaman S, 2017, original scientific article Abstract: Graphene has emerged as a potential material in various scientific disciplines, ranging from material science, engineering, and more
recently biomedicine. The paper describes the investigation of the presence of graphene and graphene oxide (GO) in the carbon soot of
internal combustion diesel engines. The UV-Visible, Fourier transform infrared (FTIR), X- ray diffraction (XRD), Photoluminescent
(PL) and Raman spectroscopic analysis of the sample provided a conclusive evidence of the formation of graphene and GO. The Field
Emission Scanning Electron Microscopy (FESEM) and Energy Dispersive Spectrum (EDX) of the sample show carbon nanoparticles
(CNPs) of size less than 50nm. The High -Resolution Transmission Electron Microscopy (HR-TEM) analysis confirmed the formation
of graphene sheets with carbon nanospheres attached to it. The study reveals the possible exploitation of the diesel soot for potential
applications in science and technology
Keywords: Graphene, Graphene oxide, Carbon nanoparticles, Combustion, Carbon nanotube
Published in RUNG: 30.06.2022; Views: 1277; Downloads: 0
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1255. Synthesis and Characterization of Carbon Nano KajalMohanachandran Nair Sindhu Swapna, 2017, short scientific article Abstract: Carbon nanoparticles are of considerable interest today because of their unique physical and biological properties. There are several
methods of preparation of Carbon Nanoparticles (CNP) with high efficacy and low toxicity. In this paper we describe a simple low cost
synthesis of carbon nanoparticle. We present a simple method for the synthesis of carbon nanoparticles from the controlled combustion of
coconut oil and ghee. The antibacterial property of CNP enables its use in kajals. The FESEM image of the sample prepared exhibit carbon
nanoparticles of size less than 50nm
Keywords: Kajal, carbon nanoparticles, soot
Published in RUNG: 30.06.2022; Views: 1090; Downloads: 0
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1256. 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: 1407; Downloads: 0
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1257. Characterization of smart and biocompatible materials based on chitosan:cellulose composites containing sporopollenin exine capsulesHanna Budasheva, Patricia Cazon Diaz, Dorota Korte, Mladen Franko, 2022, published scientific conference contribution abstract Keywords: chitosan:cellulose composites, biocompatible materials, beam deflection spectrometry, porosity determination, structural characterisation, thermal properties
Published in RUNG: 30.06.2022; Views: 1422; Downloads: 58
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1259. Boron‑rich boron carbide from soot : a low-temperature green synthesis approachMohanachandran Nair Sindhu Swapna, H. V. Saritha Devi, Sankaranarayana Iyer Sankararaman, 2020, original scientific article Abstract: Boron carbide is a promising super-hard semiconducting material for refractory applications ranging from the nuclear industry to spacecraft. The present work is the frst report of not only turning futile soot, containing carbon allotropes in varying
composition, into boron-rich boron carbide (BC), but also developing it by a low-cost, low-temperature, and green synthesis
method. The BC synthesised from gingelly oil soot is subjected to structural, morphological, and optical characterisations.
The feld emission scanning electron microscope shows beautiful fower-like morphology, and the thermogravimetric analysis reveals the high-temperature stability of the sample synthesised. The Tauc plot of the sample indicates a 2.38 eV direct
bandgap. The formation of BC and boron-rich carbide evidenced by X-ray difraction studies is confrmed through Raman
and Fourier transform infrared spectroscopic signatures of B–C and C–B–C bonds. The fuorescence, power spectrum, and
CIE analyses carried out suggest the blue light emission for excitation at 350 nm
Keywords: boron carbide, soot, carbon nanoparticle, refractory, allotropes, green synthesis
Published in RUNG: 30.06.2022; Views: 1301; Downloads: 0
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1260. Bioacoustic signal analysis through complex network featuresMohanachandran Nair Sindhu Swapna, RAJ VIMAL, Sankararaman S, 2022, original scientific article Abstract: The paper proposes a graph-theoretical approach to auscultation, bringing out the potential of graph features in
classifying the bioacoustics signals. The complex network analysis of the bioacoustics signals - vesicular (VE) and
bronchial (BR) breath sound - of 48 healthy persons are carried out for understanding the airflow dynamics
during respiration. The VE and BR are classified by the machine learning techniques extracting the graph features
– the number of edges (E), graph density (D), transitivity (T), degree centrality (Dcg) and eigenvector centrality
(Ecg). The higher value of E, D, and T in BR indicates the temporally correlated airflow through the wider
tracheobronchial tract resulting in sustained high-intense low-frequencies. The frequency spread and high-frequencies in VE, arising due to the less correlated airflow through the narrow segmental bronchi and lobar,
appears as a lower value for E, D, and T. The lower values of Dcg and Ecg justify the inferences from the spectral
and other graph parameters. The study proposes a methodology in remote auscultation that can be employed in
the current scenario of COVID-19.
Keywords: Bioacoustic signal, Graph theory, Complex network, Lung auscultation
Published in RUNG: 30.06.2022; Views: 1279; Downloads: 0
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