Deep Learning Approach for Analysis and Characterization of COVID-19

Early diagnosis of a pandemic disease like COVID-19 can help deal with a dire situation and help radiologists and other experts manage human resources more effectively. In a recent pandemic, laboratories perform diagnostics manually, which requires a lot of time and expertise of the laboratorial technicians to yield accurate results. Moreover, the cost of kits is high, and well-equipped labs are needed to perform this test. Therefore, other means of diagnosis is highly desirable. Radiography is one of the existing methods that finds its use in the diagnosis of COVID-19. The radiography observes change in Computed Tomography (CT) chest images of patients, developing a deep learning-based method to extract graphical features which are used for automated diagnosis of the disease ahead of laboratory-based testing. The proposed work suggests an Artificial Intelligence (AI) based technique for rapid diagnosis of COVID-19 from given volumetric chest CT images of patients by extracting its visual features and then using these features in the deep learning module. The proposed convolutional neural network aims to classify the infectious and non-infectious SARS-COV2 subjects. The proposed network utilizes 746 chests scanned CT images of 349 images belonging to COVID-19 positive cases, while 397 belong to negative cases of COVID-19. Our experiment resulted in an accuracy of 98.4%, sensitivity of 98.5%, specificity of 98.3%, precision of 97.1%, and F1-score of 97.8%. The additional parameters of classification error, mean absolute error (MAE), root-mean-square error (RMSE), and Matthew’s correlation coefficient (MCC) are used to evaluate our proposed work. The obtained result shows the outstanding performance for the classification of infectious and non-infectious for COVID-19 cases.     

Miniaturized Microstrip Patch Antenna Array for ISM Band Using Complementary Split Ring Resonator

Wireless Personal Communications - These days patch antenna arrays are widely used in various communication systems. In this research design of miniaturized microstrip patch antenna array is...     

Experimental investigation of particle migration in suspension flow through bifurcating microchannels

Experimental measurements of velocity and concentration profiles were carried out to study transport of non‐colloidal suspension in bifurcating micro channels for both diverging and converging flow conditions using a combination of mirco‐particle image velocimetry and particle tracking velocimetry techniques. Migration of particles across the streamline was observed and symmetric velocity and concentration profile in the inlet branch becomes asymmetric in the daughter branches. Further migration of particles toward the center of the channel in the outlet branch make the profiles again symmetric. The evolution of velocity and concentration profiles was observed to be different in the symmetric and asymmetric bifurcation channels. The comparison of the streamlines for the fluid and the particles showed significant deviation near the bifurcation region. This may explain why there is unequal flow and particle partitioning during flow of suspension in asymmetric bifurcating channels as reported in many previous studies. © 2018 American Institute of Chemical Engineers AIChE J, 64: 2293–2307, 2018     

PECVD coatings for functionalization of point-of-care biosensor surfaces

In early stage disease diagnosis, an accurate and reliable measurement of low concentrations of specific biomarkers is a key need. The detection technique requires the reaction of an antibody, which is generally covalently bound to the biosensor platform, with its antigen. The application of Zeonor^®, a cyclo olefin copolymer (COP) with very low autofluorescence, good optical properties and high precision molding characteristics, as a biosensor platform has been demonstrated recently. Highly reproducible, industrial scale surface chemical modification of the COP plastic for covalent attachment of the biomolecules for specific recognition of the target, together with low non-specific binding of other proteins that may be present in the sample is a key challenge. In this work, the applicability of plasma enhanced chemical vapor deposition (PECVD) process has been demonstrated by depositing varying surface functionalities including amines, carboxylic, mercapto, epoxy and polyethylene glycol functionalities. The plasma functionalized coatings thus created possess both reactive and repellent sites on the biosensor chip, allowing the chip to be configured either for fluorescence or light scattering-based detection or for label-free surface plasmon resonance detection techniques. The versatility of the gas phase deposition process for building sequential chemistries on low cost and disposable plastic chips is presented in detail.     

Verification of some building materials as gamma-ray shields

The shielding properties for gamma rays of a few low Z materials were investigated. The values of the mass attenuation coefficient, equivalent atomic number, effective atomic number, exposure buildup factor and energy absorption buildup factor were calculated and used to estimate the shielding effectiveness of the samples under investigation. It has been observed that the shielding effectiveness of a sample is directly related to its effective atomic number. The shielding character of any sample is a function of the incident photon energy. Good shielding behaviour has been verified in soil samples in the photon energy region of 0.015-0.30 MeV and of dolomite in 3-15 MeV. The results have been shown graphically with more useful conclusions.     

Colorimetric detection of nucleic acid signature of shiga toxin producing Escherichia coli using gold nanoparticles

Enterohemorrhagic E. coil (EHEC) serotype O157:H7 is one of the major pathogens, responsible for the severe disease outbreaks. EHEC causes diseases in humans through production of shiga-like toxin leading to bloody diarrhea. The toxin is encoded by stx2 gene in E. coli. The current methodology for detection of EHEC relies on fluorogenic-substrate based culture media or nucleic acid amplification based Real-Time Polymerase Chain Reaction assays that are either time consuming or need expensive instrumentation. In this study, the optical properties of gold nanoparticles (GNPs) have been exploited for detection of nucleic acid of Escherichia coli O157:H7. The stx2 gene representing EHEC signature has been targeted using the gold nanoparticle probes. Gold nanoparticles (GNPs) of 20 +/- 0.2 nm were synthesised by citrate reduction method and characterised by spectroscopy and transmission electron microscopy. The GNPs were functionalised with 19 and 22 bp of thiolated single stranded DNA complementary to target highly conserved 149 bp region of stx2 gene. Transmission Electron Microscopy revealed the hybridization, aggregation and reduction in the interparticle distances of the GNP probes in the presence of target DNA. The aggregation and the spectral shift in the plasmon band observed with 10(6) copies of target DNA indicates feasibility of a simple and quick colorimetric 'spot and read' test in contrast to amplification based detection methods.     

Impact of Gd Doping on Morphology and Superconductivity of NbN Sputtered Thin Films

We report the effect of Gd inclusion in the NbN superconductor thin films. The films are deposited on single crystalline Silicon (100) by DC reactive sputtering technique, i.e., deposition of Nb and Gd in presence of reactive N₂ gas. The fabricated relatively thick films (400 nm) are crystallized in cubic structure. These films are characterized for their morphology, elemental analysis, and roughness by Scanning Electron Microscopy (SEM), Energy Dispersive X-ray spectroscopy (EDAX), and Atomic Force Microscopy (AFM) respectively. The optimized film (maximum T _c ) is achieved with gas ratio of Ar:N₂ (80:20) for both pristine and Gd-doped films. The optimized NbN film possesses T _c (R=0) in zero and 140 kOe fields are at 14.8 K and 8.8 K, respectively. The Gd-doped NbN film showed T _c (R=0) in zero and 130 kOe fields at 11.2 K and 6.8 K, respectively. The upper critical field H _c2(0) of the studied superconducting films is calculated from the magneto-transport [R(T)H] measurements using GL equations. It is found that Gd doping deteriorated the superconducting performance of NbN.     

A Numerical Method for Multiphase Incompressible Thermal Flows with Solid–Liquid and Liquid–Vapor Phase Transformations

ABSTRACT

A numerical method for multiphase incompressible thermal flows with solid–liquid and liquid–vapor phase transformations is presented. The flow is mainly driven by thermocapillary force and vaporization. Based on the level set method and mixture continuum model, a set of governing equations valid for solid, liquid, and vapor phases is derived, considering phase boundary conditions as source terms in the transport equations. The vaporization process is treated as a source term in the continuity equation. The model developed is applied to the laser welding process, where the flow is coupled with optical phenomena. Formation and collapse of a laser-created hole is simulated.