Synthesis of activated charcoal from saw-dust and characterization for adsorptive separation of oil from oil-in-water emulsion

The paper represents the synthesis process of charcoal from saw dust by chemical activation with different chemical agents like phosphoric acid, zinc chloride, and ferrous sulfate heptahydrate. The synthesized charcoal samples were analyzed by scanning electron microscopy, energy dispersive X-ray spectroscopy, Fourier transform infrared spectroscopy, and BET surface analyser. The adsorption capacity of different charcoal samples was tested to separate oil from the oil-in-water emulsion. Effects of different parameters like adsorbent dosage, contact time and temperature on adsorption of oil from oil-in-water emulsion by synthesized charcoals have been investigated. Under optimized condition, the oil separation efficiency is more than 98%, though it also depends on the initial concentration of oil in the emulsion. Isotherm and kinetic study on adsorption of oil from oil-in-water emulsion have also been studied. Three widely applied isotherm models viz., Langmuir, Freundlich, and Temkin were used to analyze the experimental adsorption data. Different adsorption kinetic models were considered to model the experimental data. Thermodynamics parameters were also evaluated for the adsorption of oil onto the charcoal samples.     

Corona-Nidaan: lightweight deep convolutional neural network for chest X-Ray based COVID-19 infection detection

The coronavirus COVID-19 pandemic is today’s major public health crisis, we have faced since the Second World War. The pandemic is spreading around the globe like a wave, and according to the World Health Organization’s recent report, the number of confirmed cases and deaths are rising rapidly. COVID-19 pandemic has created severe social, economic, and political crises, which in turn will leave long-lasting scars. One of the countermeasures against controlling coronavirus outbreak is specific, accurate, reliable, and rapid detection technique to identify infected patients. The availability and affordability of RT-PCR kits remains a major bottleneck in many countries, while handling COVID-19 outbreak effectively. Recent findings indicate that chest radiography anomalies can characterize patients with COVID-19 infection. In this study, Corona-Nidaan, a lightweight deep convolutional neural network (DCNN), is proposed to detect COVID-19, Pneumonia, and Normal cases from chest X-ray image analysis; without any human intervention. We introduce a simple minority class oversampling method for dealing with imbalanced dataset problem. The impact of transfer learning with pre-trained CNNs on chest X-ray based COVID-19 infection detection is also investigated. Experimental analysis shows that Corona-Nidaan model outperforms prior works and other pre-trained CNN based models. The model achieved 95% accuracy for three-class classification with 94% precision and recall for COVID-19 cases. While studying the performance of various pre-trained models, it is also found that VGG19 outperforms other pre-trained CNN models by achieving 93% accuracy with 87% recall and 93% precision for COVID-19 infection detection. The model is evaluated by screening the COVID-19 infected Indian Patient chest X-ray dataset with good accuracy.

     

Structural and Dielectric Properties of PVP Based Composite Polymer Electrolyte Thin Films

The study and application of thin film technology is entirely entered in to almost all the branches of science and technology. Transparent conducting oxide films have been widely used in the fields of flat panel displays, solar cells, touch panels and other optoelectronic devices owing to their high electrical conductivity and optical transmittance in visible region. In the present study, Solid state ion conducting polymer electrolyte films were prepared by doping nano-sized TiO₂ particles on PVP (poly vinyl pyrrolidone) complexed with MgSO₄·7H₂O salt by solution casting technique and characterized by powder XRD, DSC, SEM, optical and dielectric studies. The XRD pattern of the prepared sample shows the semi-crystalline nature. SEM and EDS confirms the presence of compounds inside the material. Optical absorption studies are used to measure the bandgap of the prepared sample. Dielectric studies are performed to observe the conductivity of the sample.     

Effect of γ‐ray irradiation on morphology and electrical properties of poly(vinyl chloride)/graphite composites

This article reports the effect of crosslinking by γ‐ray irradiation on the morphology, electrical properties, and hardness of poly(vinyl chloride)/graphite composite. A comparison of the scanning electron micrographs of the composites, before and after irradiation, showed that the filler particles were broken into pieces and distributed homogenously as a result of irradiation. The data of electrical conductivity versus graphite content was found to be consistent with the percolation model. A significant increase in the conductivity of composite was observed on the crosslinking of the polymer in consequence of irradiation. The data are correlated with the morphological changes. The study of electrical resistivity as a function of temperature revealed that the negative temperature coefficient of resistivity effect is considerably suppressed after irradiation. These results are explained on the basis of morphological changes in the composites after γ‐ray irradiation. POLYM. ENG. SCI., 2009. © 2009 Society of Plastics Engineers     

Studies on La0.67Ca0.33MnO3-SrTiO3 composites using two-phase model

In this study we report the structural, electrical and magnetic properties of (1 − x)La_0.67Ca_0.33MnO₃ (LCMO)-(x)SrTiO₃(STO) composites. For this series we have observed a minute change in ferromagnetic (FM)-paramagnetic (PM) transition temperature with STO addition in LCMO matrix; however a reasonable change is observed in metal-insulator transition temperature, along with the occurrence of percolation threshold for x = 0.30 sample. Overall pattern for temperature dependence of resistivity for this series has been best-fitted using the formula 1/ρ = (1 − f)/ρ_PM + (f/ρ_FM), whereρ_PM and ρ_FM are the resistivities of the PM and FM contents in the sample and f is the volume fraction of FM phase in the sample. Investigations on magnetoresistance (MR) using magnetic field up to 3 T show enhancement of extrinsic MR in the composite samples which can be viewed in the light of spin polarized tunneling.     

Stereochemical assignments of the nuclear magnetic resonance spectra of isobornyl acrylate/methacrylonitrile copolymers

Isobornyl acrylate (B)/methacrylonitrile (N) copolymers with different compositions were synthesized by the free‐radical bulk polymerization with azobisisobutyronitrile as the initiator under a nitrogen atmosphere at 70°C. The copolymer compositions were calculated from quantitative ¹³C(¹H)NMR spectra. The reactivity ratios of the comonomers in the B/N copolymers determined from the linear Kelen–Tudos method and nonlinear error‐in‐variable method were r_B = 0.66 ± 0.11 and r_N = 1.54 ± 0.22 and r_B = 0.74 and r_N = 1.65, respectively. The complete spectral assignments of the ¹H‐NMR and ¹³C(¹H)‐NMR spectra were carried out with the help of distortionless enhancement by polarization transfer, two‐dimensional (2D) heteronuclear single quantum coherence, and 2D total correlation spectroscopy. The nitrile carbon of the N unit and the methine and OCH carbons of the B unit were assigned to triad compositional sequences, whereas the β‐methylene carbons of the B and N units were assigned to the tetrad compositional and configurational sequences. The α‐methyl carbon of the N unit was also assigned to the triad level of configurational and compositional sequences. Similarly, the nitrile and quaternary carbon resonances with the methine, methylene, and methyl protons were studied in detail with 2D heteronuclear multiple‐bond correlation spectra. © 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Molecular Cloning and Sequence Analysis of Bile Salt Hydrolase Gene (bsh) from Lactobacillus plantarum MBUL90 Strain of Human Origin

This study provided genetic information on a bile salt hydrolase (bsh) of a Lactobacillus plantarum strain of Indian origin, MBUL90. L. plantarum strains were screened by PCR for the determination of the bsh locus in their genome using specific primers. None of the lactobacilli strains produced the expected size of amplicon (～ 1.0 kb) except L. plantarum strains, which proved the specificity of the primers. The bsh amplicon of L. plantarum MBUL90 was cloned into pDrive vector, and nucleotide sequences were determined. Sequence analysis of bsh genes revealed a high level of similarity within the species of L. plantarum as well as with other species of Lactobacillus. The resulting nucleotide sequence of an ORF of 975 bp encoded a predicted protein of 324 amino acids representing a theoretical molecular mass of 37 kDa with a pI of 4.92. The protein deduced from the complete ORF had high similarity with other Bsh proteins, and four highly conserved amino acid motifs (YFGRNXD, NEXGLXXAGLNF, VXVLTNNPXF, and SXSRFVRXAF) were located around the active site. Genetic data presented in this paper provide a sound foundation for better understanding the genetic diversity of bsh in Lactobacillus genus and may provide a new genetic marker for phylogenetic study.     

Improving the low temperature properties of biodiesel fuel

The use of biodiesel as a diesel fuel extender and lubricity improver is rapidly increasing. While most of the properties of biodiesel are comparable to petroleum based diesel fuel, improvement of its low temperature flow characteristic still remains one of the major challenges when using biodiesel as an alternative fuel for diesel engines. The biodiesel fuels derived from fats or oils with significant amounts of saturated fatty compounds will display higher cloud points and pour points. This paper is aimed to investigate the cold flow properties of 100% biodiesel fuel obtained from Madhuca indica, one of the important species in the Indian context. In this paper, the cold flow properties of biodiesel were evaluated with and without pour point depressants towards the objectives of identifying the pumping and injecting of these biodiesel in CI engines under cold climates. Effect of ethanol, kerosene and commercial additive on cold flow behavior of this biodiesel was studied. A considerable reduction in pour point has been noticed by using these cold flow improvers. The performance and emission with ethanol blended Mahua biodiesel fuel and ethanol–diesel blended Mahua biodiesel fuel have also been studied. A considerable reduction in emission was obtained. Ethanol blended biodiesel is totally a renewable, viable alternative fuel for improved cold flow behavior and better emission characteristics without affecting the engine performance.     

A Bayesian multiple-hypothesis approach to edge grouping and contour segmentation

A contour segmentation algorithm is presented that takes an edge map and extracts continuous curves of arbitrary smoothness, correctly handling curve intersections and capable of extrapolating over significant measurement gaps. The algorithm incorporates noise models of the edge-detection process and limited scene statistics. It is based on an explicit contour model and employs a statistical distance measure to quantify the likelihood of each segmentation hypothesis. A Bayesian multiple-hypothesis tree organizes possible segementations, making it possible to postpone grouping decisions until a sufficient amount of information is available. We have demonstrated its performance on real and synthetic images.