Ninan Sajeeth Philip | Cochin University of Science and Technology (original) (raw)

Papers by Ninan Sajeeth Philip

This is a complete rewrite of the previous development version of CASSPER for academic and reseaa... more This is a complete rewrite of the previous development version of CASSPER for academic and reseaarch audiance. The installation and usage procedures are simplified. The toolkit may be run as a Python module and the required packages are installed from the Internet to the system when it is first executed. This makes it easier for users to get started. A detailed user manual with walk through examples are included to flatten the learning curve.

The natural products have provided considerable value to the pharmaceutical industry over the pas... more The natural products have provided considerable value to the pharmaceutical industry over the past century and its demand is steadily increasing. This is mainly attributed to several factors; unachieved therapeutic needs, demand for bulk supplies and great impact of herbal remedies in the global market. Essential oils or essences have an extraordinary range of pharmacological activities including antiallergic, antiin:flarnmatory, antimutagenic and antimicrobial activities. Essential oils find uses in pharmaceutics, cosmaceutics and aromatherapy. Essential oils can be obtained by cold press extraction, steam distillation, supercritical fluid extraction and solvent extraction. The objectives of the study were to characterise th.e composition of essential oils from different plant parts of Tasmanian Callitris spp C. rhomboidea and C. oblonga, to identify some of the major unknown constituents in the root oil, to investigate the composition of the solvent extracts, to investigate the biological activities of the C. rhomboidea and C. oblonga SD oils and extracts against a range of bacteria and fungi, to investigate the release of essential oils from C. rhomboidea roots in situ, and to investigate the allelopathic activities of C. rhomboidea and C. oblonga root and leaf oils. Volatile fractions from the roots, leaves, bark and fruits of Callitris oblonga and Callitris rhomboidea were obtained by steam distillation (SD) and solvent extraction with petroleum ether (PE) and dichloromethane (DCM). Essential oil composition was analysed by gas chromatography-mass spectrometry (GC-MS) and gas chromatography-flame ionisation detection (GC-FID). Thirty six c9mpounds, representing 85% of the steam distillate from C. rhomboidea roots, and 45 compounds representing 90% of the steam distillate from the C. oblonga roots were identified. Sesquiterpene hydrocarbons constituted the major portion of Callitris spp. root oils. The main identified constituents found in the SD root oil of C. rhomboidea were longiborneol (23%) and longifolene (5%); the main constituent from SD root oil of C. oblonga was columellarin (30%). In the SD fraction of the C. rhomboidea leaf apinene (42%), geranyl acetate (12%), citronellyl acetate (7%) and neryl acetate (6%) were the major constituents. C. oblonga SD leaf oil contained significant amount of a-pinene (45%), isopulegol (6%) and pulegol (2%). The major components in the fruit and bark oil of the Callitris spp. were monoterpenes such as a-and ,8-pinenes. III Solvent extracts contained a high percentage of diterpenes. However the maJor compounds analysed by GC-MS from the SD fractions of the respective plant organs were also present in their respective solvent extracts. Experiments were performed on collected roots and leaves ('in vial'. experiments) and on intact roots of Callitris plants to investigate the release of volatiles utilising solid phase microextraction (SPME). A soil probe designed and manufactured inhouse was used for the study of volatiles evolved from the intact roots. Model experiments using known quantities of volatiles adsorbed onto sand were performed to determine the efficiency of the soil probe. Analysis of 'in vial' SPME sample experiments of roots demonstrated a release pattern of volatiles characterstic of the respective root oils; while leaf sample 'in vial' analysis did not show a characterstic pattern of their respective leaf oils. In situ samplings were done from 2 trees growing at different locations. GC-MS analysis of both samples demonstrated the presence of petrochemical-like hydrocarbons. The samples collected from the second site demonstrated the presence of monoterpene hydrocarbons. These monoterpenes were present in the same ratios as in the steam distilled root oils. Antimicrobial screening of Callitris essential oils, leaf oil fractions and extracts of different organs of Callitris spp. was performed against the bacteria Staphylococcus aureus, Bacillus subtilis, Staphylococcus epidermis, Dermatophilus congolensis,

Astronomy and Astrophysics, Apr 1, 2002

In this paper we describe the use of a new artificial neural network, called the difference boost... more In this paper we describe the use of a new artificial neural network, called the difference boosting neural network (DBNN), for automated classification problems in astronomical data analysis. We illustrate the capabilities of the network by applying it to star galaxy classification using recently released, deep imaging data. We have compared our results with classification made by the widely used Source Extractor (SExtractor) package. We show that while the performance of the DBNN in star-galaxy classification is comparable to that of SExtractor, it has the advantage of significantly higher speed and flexibility during training as well as classification.

Physica Status Solidi A-applications and Materials Science, Oct 1, 2007

Ga-doped ZnO (GZO)/ZnO bi-layered films were deposited on glass substrates by radio frequency mag... more Ga-doped ZnO (GZO)/ZnO bi-layered films were deposited on glass substrates by radio frequency magnetron sputtering at different substrate temperatures of 100, 200 and 300 1C to investigate the effects of substrate temperature on the structural, electrical, and optical properties of the films. Thicknesses of the GZO and ZnO buffer layer were kept constant at 85 and 15 nm by controlling the deposition times. The films deposited at room temperature had a relatively low optical transmittance of 80.5%, while films deposited at substrate temperature of 300 1C showed a higher transmittance of 84.5% compared to the other films. Electrical resistivity of the films was also influenced by substrate temperature and the lowest resistivity of 2.7 Â 10 À 3 Ω cm was observed for films deposited at 300 1C. The observed result means that increasing the substrate temperature enhanced the optical transmittance and electrical conductivity of GZO/ZnO bi-layered films, simultaneously.

Intelligent Data Analysis, Dec 22, 2000

Computers & Geosciences, Mar 1, 2003

Rainfall, like all other natural phenomena is highly unpredictable. Traditionally, principal comp... more Rainfall, like all other natural phenomena is highly unpredictable. Traditionally, principal component analysis and spectral analysis are used to understand trends in rainfall over long periods. In this paper, we present a new method that appears to be better than existing methods to ...

Physical review, May 31, 2017

Detection and classification of transients in data from gravitational wave detectors are crucial ... more Detection and classification of transients in data from gravitational wave detectors are crucial for efficient searches for true astrophysical events and identification of noise sources. We present a hybrid method for classification of short duration transients seen in gravitational wave data using both supervised and unsupervised machine learning techniques. To train the classifiers we use the relative wavelet energy and the corresponding entropy obtained by applying one-dimensional wavelet decomposition on the data. The prediction accuracy of the trained classifier on nine simulated classes of gravitational wave transients and also LIGO's sixth science run hardware injections are reported. Targeted searches for a couple of known classes of non-astrophysical signals in the first observational run of Advanced LIGO data are also presented. The ability to accurately identify transient classes using minimal training samples makes the proposed method a useful tool for LIGO detector characterization as well as searches for short duration gravitational wave signals.

The amount of collected data in many scientific fields is increasing, all of them requiring a com... more The amount of collected data in many scientific fields is increasing, all of them requiring a common task: extract knowledge from massive, multi parametric data sets, as rapidly and efficiently possible. This is especially true in astronomy where synoptic sky surveys are enabling new research frontiers in the time domain astronomy and posing several new object classification challenges in multi dimensional spaces; given the high number of parameters available for each object, feature selection is quickly becoming a crucial task in analyzing astronomical data sets. Using data sets extracted from the ongoing Catalina Real-Time Transient Surveys (CRTS) and the Kepler Mission we illustrate a variety of feature selection strategies used to identify the subsets that give the most information and the results achieved applying these techniques to three major astronomical problems.

arXiv (Cornell University), Aug 10, 2010

A learning algorithm based on primary school teaching and learning is presented. The methodology ... more A learning algorithm based on primary school teaching and learning is presented. The methodology is to continuously evaluate the performance of the network and to train it on the examples for which they repeatedly fail, until, all the examples are correctly classified. Empirical analysis on UCI data show that the algorithm produces a good training data and improves the generalization ability of the network on unseen data. The algorithm has interesting applications in data mining, model evaluations and rare objects discovery.

arXiv (Cornell University), May 31, 2000

Lecture Notes in Computer Science, 2001

This paper surveys and places into perspective a number of results concerning the D-BSP (Decompos... more This paper surveys and places into perspective a number of results concerning the D-BSP (Decomposable Bulk Synchronous Parallel) model of computation, a variant of the popular BSP model proposed by Valiant in the early nineties. D-BSP captures part of the proximity structure of the computing platform, modeling it by suitable decompositions into clusters, each characterized by its own bandwidth and latency parameters. Quantitative evidence is provided that, when modeling realistic parallel architectures, D-BSP achieves higher effectiveness and portability than BSP, without significantly affecting the ease of use. It is also shown that D-BSP avoids some of the shortcomings of BSP which motivated the definition of other variants of the model. Finally, the paper discusses how the aspects of network proximity incorporated in the model allow for a better management of network congestion and bank contention, when supporting a shared-memory abstraction in a distributed-memory environment.

arXiv (Cornell University), Feb 16, 2001

This paper discusses mixing of chaotic systems as a dependable method for secure communication. D... more This paper discusses mixing of chaotic systems as a dependable method for secure communication. Distribution of the entropy function for steady state as well as plaintext input sequences are analyzed. It is shown that the mixing of chaotic sequences results in a sequence that does not have any state dependence on the information encrypted by them. The generated output states of such a cipher approach the theoretical maximum for both complexity measures and cycle length. These features are then compared with some popular ciphers.

Neurocomputing, Aug 1, 2002

It is shown that modifying the sigmoidal basis function of a multi-layer feedforward arti"cial ne... more It is shown that modifying the sigmoidal basis function of a multi-layer feedforward arti"cial neural network using a control parameter improves the network's ability to learn. The modi"cation is rendered by a gradient descent algorithm similar to the back-propagation. In doing so, the method retains all the goodies of the sigmoidal function and causes the ANN to approximate the decision function faster and also with better accuracy.

IEEE Transactions on Plasma Science

VizieR Online Data Catalog, Jun 1, 2021

Communications Biology, 2021

Particle identification and selection, which is a prerequisite for high-resolution structure dete... more Particle identification and selection, which is a prerequisite for high-resolution structure determination of biological macromolecules via single-particle cryo-electron microscopy poses a major bottleneck for automating the steps of structure determination. Here, we present a generalized deep learning tool, CASSPER, for the automated detection and isolation of protein particles in transmission microscope images. This deep learning tool uses Semantic Segmentation and a collection of visually prepared training samples to capture the differences in the transmission intensities of protein, ice, carbon, and other impurities found in the micrograph. CASSPER is a semantic segmentation based method that does pixel-level classification and completely eliminates the need for manual particle picking. Integration of Contrast Limited Adaptive Histogram Equalization (CLAHE) in CASSPER enables high-fidelity particle detection in micrographs with variable ice thickness and contrast. A generalized ...

Advances in Space Research, 2021

Abstract A shock wave can be formed by continuous mass loading of the solar wind by the newly for... more Abstract A shock wave can be formed by continuous mass loading of the solar wind by the newly formed cometary ions. The formation of ion acoustic shocklets has thus been studied in a plasma of solar and cometary electrons, described by kappa distribution functions with different temperatures and spectral indices, a drifting H 3 O + ion component and a pair of oppositely charged oxygen ion components. The Korteweg-deVries-Burger’s equation which describes weakly nonlinear waves in a dissipative medium has been derived for the above plasma composition using the momentum, continuity and Poisson’s equations and studied for parameters observed at the inner shock region of comet Halley. We find that the spectral index of the cometary electrons plays a key role in the formation, speed of propagation and width of the shock wave, which has been interpreted as a “shocklet”, whose strength decreases as the spectral indices increase or as the suprathermal distribution relaxes to a Maxwellian distribution, with a buildup of colder electrons. Also, all three components of ions contribute to the formation of shocklets; thus bringing out the additive nature of the contributions of various types of ions to their formation. This study could aid the understanding of in-situ measurements of shock waves in cometary plasmas.

Research & Reviews: Journal of Physics, 2019

We studied dust acoustic solitary waves (DASW) in a five component cometary plasma by deriving th... more We studied dust acoustic solitary waves (DASW) in a five component cometary plasma by deriving the Kadomstev-Petiashvili (KP) equation. The five components consist of two components of electrons described by kappa distributions with different temperatures and spectral indices, a lighter (hydrogen) and a heavier (oxygen) ion component, both ion components are described by Maxwellian distributions. Dust particles, with varying charge, constitute the fifth component. The system supports rarefactive DASWs whose amplitudes are larger when the charges on the dust particles vary. The amplitudes also increase with increasing z d0 n d0 (product of equilibrium charge number and density of dust) and increasing ion densities. It, however, decreases with increasing spectral indices of the electrons.

The Astrophysical Journal, 2016

We report the detection of large variations in the outflow wind velocity from a young eruptive st... more We report the detection of large variations in the outflow wind velocity from a young eruptive star, V899 Mon during its ongoing high accretion outburst phase. Such large variations in the outflow velocity (from-722 km s −1 to-425 km s −1) have never been reported previously in this family of objects. Our continuous monitoring of this source shows that the multi-component, clumpy, and episodic high velocity outflows are stable in the time scale of a few days, and vary over the time scale of a few weeks to months. We detect significant decoupling in the instantaneous outflow strength to accretion rate. From the comparison of various possible outflow mechanisms in magnetospheric accretion of young stellar objects, we conclude magnetically driven polar winds to be the most consistent mechanism for the outflows seen in V899 Mon. The large scale fluctuations in outflow over the short period makes V899 Mon the most ideal source to constrain various magnetohydrodynamics (MHD) simulations of magnetospheric accretion.