Salil Kumar Biswas

Bio: Salil Kumar Biswas is an academic researcher from University of Calcutta. The author has contributed to research in topics: Microwave cavity & Dielectric. The author has an hindex of 7, co-authored 17 publications receiving 121 citations.

Identification and analysis of coding and non-coding regions of a DNA sequence by positional frequency distribution of nucleotides (PFDN) algorithm

Abstract: During the last several years, substantial progress has been made in developing high-throughput experimental techniques that produce large amounts of genomic data pertaining to molecular activities in cells. Consequently, a great deal of research is being focused on addressing important problems in molecular biology by analyzing these data using mathematical and computational approaches. Genomic signal processing has been an active area of research for the past two decades and have increasingly attracted the attention of researchers from digital signal processing area all over the world. An important step in genomic annotation is to identify protein coding regions of DNA sequence especially in the study of eukaryotic genomes. Due to lack of obvious sequence features among exons and introns, distinguishing protein coding regions from non-coding regions effectively is a challenging problem. A variety of computational algorithms have been developed to predict exons. Most of the exon finding algorithms are based on statistics methods. The signal processing approaches of recent years may identify some hidden periodicity and features which can not be revealed easily by conventional statistics methods. In this paper the authors have presented an algorithm to separate out coding regions from non-coding regions based on positional frequency distribution of nucleotides and the algorithm shows the results that exon regions exhibit more random behavior compared to intron regions. Such a behavior was also observed by FFT power spectrum analysis of DNA sequences. Case studies on genes from different organisms show that the algorithm is an effective approach towards exon prediction.

Simple theoretical analysis of the thermoelectric power under strong magnetic quantization in superlattices of non-parabolic semiconductors with graded interfaces

Abstract: An attempt is made in this paper to present a simple theoretical analysis of the thermoelectric power under strong magnetic quantization (TPM) in III–V, II–VI, PbTe/PbSnTe, strained layer and HgTe/CdTe superlattices (SLs) with graded interfaces and compare the same with that of the constituent materials by formulating the respective magneto dispersion laws, which in turn control all the transport properties through Bolzmann transport equation. It has been observed, taking GaAs/Ga 1− x Al x As, CdS/CdTe, PbTe/PbSnTe, InAs/GaSb and HgTe/CdTe with graded interfaces as examples, that the TPM exhibits oscillatory dependence with the inverse quantizing magnetic field due to the SdH and allied SL effects and increases with increasing inverse electron concentration in an oscillatory manner in all the cases. The nature of oscillation is totally band structure dependent and the width of the finite interface enhances the numerical values of the TPM for all the aforementioned SLs. The numerical values of the TPM in graded SLs are greater than that of the constituent materials. The theoretical results are in quantitative agreement with the experimental results as given elsewhere. The well-known expressions for the bulk specimens of wide-gap materials can also be obtained as special cases of our generalized analysis under certain limiting conditions. In addition, we have suggested the experimental methods of determining the Einstein relation for diffusivity–mobility ratio, the Debye screening length and carrier contribution to the elastic constants, respectively, for materials having arbitrary dispersion laws.

Identification and analysis of coding and non-coding regions of a DNA sequence by positional frequency distribution of nucleotides (PFDN) algorithm

Abstract: During the last several years, substantial progress has been made in developing high-throughput experimental techniques that produce large amounts of genomic data pertaining to molecular activities in cells. Consequently, a great deal of research is being focused on addressing important problems in molecular biology by analyzing these data using mathematical and computational approaches. Genomic signal processing has been an active area of research for the past two decades and have increasingly attracted the attention of researchers from digital signal processing area all over the world. An important step in genomic annotation is to identify protein coding regions of DNA sequence especially in the study of eukaryotic genomes. Due to lack of obvious sequence features among exons and introns, distinguishing protein coding regions from non-coding regions effectively is a challenging problem. A variety of computational algorithms have been developed to predict exons. Most of the exon finding algorithms are based on statistics methods. The signal processing approaches of recent years may identify some hidden periodicity and features which can not be revealed easily by conventional statistics methods. In this paper the authors have presented an algorithm to separate out coding regions from non-coding regions based on positional frequency distribution of nucleotides and the algorithm shows the results that exon regions exhibit more random behavior compared to intron regions. Such a behavior was also observed by FFT power spectrum analysis of DNA sequences. Case studies on genes from different organisms show that the algorithm is an effective approach towards exon prediction.

On the modification of the Fermi-Dirac distribution function in degenerate semiconductors

Abstract: An attempt is made to study the Fermi–Dirac distribution function in degenerate semiconductors forming band tails (fp) on the basis of a newly formulated electron dispersion law. It appears, taking n-GaAs as an example, that the influence of the carrier concentration (Ni) on fp is more significant than that of f0 and fp is more effective than f0 for higher values of Ni. The relative change in Fermi–Dirac function with respect to f 0 ( ( Δ f / f 0 ) , Δ f = f p - f 0 ) for a fixed value of impurity screening potential, has initially zero value and then decreases with increasing electron energy (E). Thereafter exhibiting the minimum value, the ( Δ f / f 0 ) increases at a relatively slow rate with increasing E and for higher value of E , fp approaches to f0. The present formulation provides us the key to investigate the transport properties of degenerate semiconductors which, in turn, depend on the solution of the Boltzmann transport equation and is expected to agree better with the experiments.

Dielectric properties of EVA rubber composites at microwave frequencies theory, instrumentation and measurements.

Abstract: This work describes and evaluates a technique for determining the dielectric properties of carbon-black filled Ethylene Vinyl Acetate (EVA) rubber and presents results on the studies of the effect of frequency on the permittivity and microwave conductivity using resonant cavity perturbation method. The measurements are performed with the aid of a Network Analyzer in X-band. The simplicity of this method lies in the fact that the dielectric properties can be obtained directly from the analytical formula without taking recourse to calibration.

A Self-Sustained CMOS Microwave Chemical Sensor Using a Frequency Synthesizer

Abstract: In this paper, a CMOS on-chip sensor is presented to detect dielectric constant of organic chemicals. The dielectric constant of these chemicals is measured using the oscillation frequency shift of an LC voltage-controlled oscillator (VCO) upon the change of the tank capacitance when exposed to the liquid. To make the system self-sustained, the VCO is embedded inside a frequency synthesizer to convert the frequency shift into voltage that can be digitized using an on-chip analog-to-digital converter. The dielectric constant is then estimated using a detection procedure including the calibration of the sensor. The dielectric constants of different organic liquids have been detected in the frequency range of 7-9 GHz with an accuracy of 3.7% compared with theoretical values for sample volumes of 10-20 μL. The sensor is also applicable for binary mixture detection and estimation of the fractional volume of the constituting materials with an accuracy of 1%-2%.

A 1–8-GHz Miniaturized Spectroscopy System for Permittivity Detection and Mixture Characterization of Organic Chemicals

Abstract: In this paper, a miniaturized broadband dielectric spectroscopy system is presented for permittivity detection, chemical sensing, and mixture characterization for 1-8-GHz frequency range. A sensing capacitor exposed to the material under test (MUT) is part of a true time-delay (TTD) cell excited by a microwave signal at the sensing frequency of interest. The phase shift of the microwave signal at the output of the TTD cell compared to its input is a measure of the permittivity of MUTs. For wideband and accurate sensing, TTD cells are cascaded in a reconfigurable fashion to increase the detected phase shift, especially at low frequencies. TTD cells are designed to detect permittivities within the range of 1-30 considering nonideal effects, such as electromagnetic coupling between adjacent TTD cells. Calibration using reference liquids is applied to the fabricated sensor and sensor characteristics are extracted. Permittivity detection of organic chemicals is performed in the range of 1-8 GHz with an error less than 2%. The measured permittivities in the 1-8-GHz range are used to estimate the sub-1-GHz permittivities of MUTs using extrapolation. The sensing system is also used for mixture characterization to find the mixing ratios in binary mixtures with an accuracy of 1%.

Integrated Systems for Biomedical Applications: Silicon-Based RF\/Microwave Dielectric Spectroscopy and Sensing

Abstract: Recent multi-disciplinary research focuses on expanding the use of integrated electronic circuits and systems in nonelectrical applications such as chemical/biomedical sensors. The global trend in this area is moving toward portable, implantable, and lab-on-chip systems that require 1) complete integration of the system-on-silicon platforms, such as complementary-metal-oxide-semiconductor (CMOS) processes, and 2) self-sustained implementation to achieve stand-alone operation without the need for any external equipment. In other words, self-sustained, integrated systems are necessary for portable and implantable sensors.

Acceptor-modulated optical enhancements and band-gap narrowing in ZnO thin films

Abstract: Fermi-Dirac distribution for doped semiconductors and Burstein-Moss effect have been correlated first time to figure out the conductivity type of ZnO. Hall Effect in the Van der Pauw configuration has been applied to reconcile our theoretical estimations which evince our assumption. Band-gap narrowing has been found in all p-type samples, whereas blue Burstein-Moss shift has been recorded in the n-type films. Atomic Force Microscopic (AFM) analysis shows that both p-type and n-type films have almost same granular-like structure with minor change in average grain size (∼ 6 nm to 10 nm) and surface roughness rms value 3 nm for thickness ∼315 nm which points that grain size and surface roughness did not play any significant role in order to modulate the conductivity type of ZnO. X-ray diffraction (XRD), Energy Dispersive X-ray Spectroscopy (EDS) and X-ray Photoelectron Spectroscopy (XPS) have been employed to perform the structural, chemical and elemental analysis. Hexagonal wurtzite structure has been observed in all samples. The introduction of nitrogen reduces the crystallinity of host lattice. 97% transmittance in the visible range with 1.4 × 107 Ω-1cm-1 optical conductivity have been detected. High absorption value in the ultra-violet (UV) region reveals that NZOs thin films can be used to fabricate next-generation high-performance UV detectors.