Indian Institute of Technology Palakkad&nbsp;(IIT Palakkad or IIT PKD) is a public autonomous&nbsp;engineering&nbsp;and&nbsp;research&nbsp;institute located in&nbsp;Palakkad,&nbsp;Kerala. It was&nbsp;one of the five new&nbsp;IITs&nbsp;proposed in the&nbsp;2014 Union budget of India. The campus was inaugurated on 3 August 2015. The institute has 94 faculty, 978 students, and 63 non-teaching staffs.

IT Palakkad currently offers four-year Bachelor of Technology (B.Tech) and two years MS programmes in 8 different engineering disciplines including&nbsp;Computer Science, Electrical, Mechanical, Civil among others.

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IIT Palakkad

Given an undirected simple graph G, a set of vertices is an r-clique transversal if it has at least one vertex from every r-clique. Such sets generalize vertex covers as a vertex cover is a 2-clique transversal. Perfect graphs are a well-studied class of graphs on which a minimum weight vertex cover can be obtained in polynomial time. Further, an r-clique transversal in a perfect graph is also a set of vertices whose deletion results in an (r- 1) -colorable graph. In this work, we study the problem of finding a minimum weight r-clique transversal in a perfect graph. This problem is known to be NP-hard for r≥ 3 and admits a straightforward r-approximation algorithm. We describe two different r+12-approximation algorithms for the problem. Both the algorithms are based on (different) linear programming relaxations. The first algorithm employs the primal–dual method while the second uses rounding based on a threshold value. We also show that the problem is APX-hard and describe hardness results in the context of parameterized algorithms and kernelization. © 2017, Springer Science+Business Media New York.

World University root node

Department of Computer Science and Engineering

Algorithmica

Approximability of Clique Transversal in Perfect Graphs

The synthesis, photophysics and biological investigation of fluorescent 4-amino-1,8-naphthalimide Tröger's bases (TB-1-TB-3) and a new Tröger's base p-cymene-Ru(ii)-curcumin organometallic conjugate (TB-Ru-Cur) are described; these compounds showed fast cellular uptake and displayed good luminescence and cytotoxicity against cervical cancer cells. © 2018 The Royal Society of Chemistry.

Department of Chemistry

Fulltext

Chemical Communications

Synthesis, structural characterisation and antiproliferative activity of a new fluorescent 4-amino-1,8-naphthalimide Tröger's base-Ru(ii)-curcumin organometallic conjugate

Introduction: Vaccinology has evolved from a sub-discipline focussed on simplistic vaccine development based on antibody-mediated protection to a separate discipline involving epidemiology, host and pathogen biology, immunology, genomics, proteomics, structure biology, protein engineering, chemical biology, and delivery systems. Data mining in combination with bioinformatics has provided a scaffold linking all these disciplines to the design of vaccines and vaccine adjuvants. Areas covered: This review provides background knowledge on immunological aspects which have been exploited with informatics for the in silico analysis of immune responses and the design of vaccine antigens. Furthermore, the article presents various databases and bioinformatics tools, and discusses B and T cell epitope predictions, antigen design, adjuvant research and systems immunology, highlighting some important examples, and challenges for the future. Expert opinion: Informatics and data mining have not only reduced the time required for experimental immunology, but also contributed to the identification and design of novel vaccine candidates and the determination of biomarkers and pathways of vaccine response. However, more experimental data is required for benchmarking immunoinformatic tools. Nevertheless, developments in immunoinformatics and reverse vaccinology, which are nascent fields, are likely to hasten vaccine discovery, although the path to regulatory approval is likely to remain a necessary impediment. © 2017 Informa UK Limited, trading as Taylor &amp; Francis Group.

Biological Sciences and Engineering

Expert Opinion on Drug Discovery

The use of databases, data mining and immunoinformatics in vaccinology: where are we?

Signaling Lymphocytic Activation Molecules (SLAM) family receptors are initially described in immune cells. These receptors recruit both activating and inhibitory SH2 domain containing proteins through their Immunoreceptor Tyrosine based Switch Motifs (ITSMs). Accumulating evidence suggest that the members of this family are intimately involved in different physiological and pathophysiological events such as regulation of immune responses and entry pathways of certain viruses. Recently, other functions of SLAM, principally in the pathophysiology of neoplastic transformations have also been deciphered. These new findings may prompt SLAM to be considered as new tumor markers, diagnostic tools or potential therapeutic targets for controlling the tumor progression. In this review, we summarize the major observations describing the implications and features of SLAM in oncology and discuss the therapeutic potential attributed to these molecules. © Fouquet et al.

Oncotarget

Signaling lymphocytic activation molecules Slam and cancers: Friends or foes?

Cellular and Molecular Immunology

Induction of human dendritic cell maturation by naïve and memory B-cell subsets requires different activation stimuli

MEDICAL MYCOLOGY

Two Aspergillus species, A. flavus and A. fumigatus - a comparative study of their conidial surface properties and immunological reactivities

Conventional voltage-source inverters used for induction motor drives generate a hexagonal space vector structure. In the overmodulation range, the hexagonal space vector structure generates low-order harmonics in the phase voltage resulting in low-order torque ripple in the motor. Inverter topologies with an octadecagonal (18 sided) space vector structure eliminate fifth-, seventh-, eleventh-, and thirteenth-order harmonics from the phase voltage, and hence, the dominant sixth- and twelfth-order torque ripple generation is eliminated. Octadecagonal space vector structures proposed in the past require multiple dc sources, which makes four-quadrant operation of the drive system difficult and costly. In this paper, the formation of a multilevel nine-concentric octadecagonal space vector structure using a single dc source is proposed. Detailed experimental results, using open-loop V/f control and rotor field-oriented control, are presented to validate the effectiveness of the proposed drive scheme. © 2017 IEEE.

Department of Electrical Engineering

IEEE Transactions on Power Electronics

A Low-Order Harmonic Elimination Scheme for Induction Motor Drives Using a Multilevel Octadecagonal Space Vector Structure With a Single DC Source

In this paper, we show how the presence of locality within a binary cyclic code can be exploited to improve decoding performance and to reduce decoding complexity. We pursue two approaches. Under the first approach, we show how the ordered statistics decoding (OSD) method can be modified by inserting a simple single round belief-propagation step at the start that involves only the local codes. The resultant locality-aware OSD algorithm yields an appreciable signal-to-noise ratio (SNR) gain for a given level of reliability and essentially the same level of decoder complexity. Under the second, trellis decoding approach, we show that the careful introduction of locality results in the creation of a cyclic subcode that possesses lower maximum state complexity. In addition, we present a simple means of deriving an upper bound to the state complexity profile of any cyclic code that is based only on the zeros of the code. Furthermore, we show how the decoding speed of either locality-aware OSD or trellis decoding can be significantly increased in the presence of locality, in the moderate-to-high SNR regime, by making the use of a quick-look decoder that often returns the maximum likelihood code word. © 1972-2012 IEEE.

Department of Data Science

IEEE Transactions on Communications

Exploiting Locality for Improved Decoding of Binary Cyclic Codes

Orthogonal frequency-division multiplexing (OFDM) is a multi-carrier modulation scheme that has been employed in many communication standards. The performance of OFDM is severely degraded by the presence of impulsive noise caused due to different nonlinear devices and power amplifiers. In this paper, we propose a novel automated framework to detect and remove impulse noise in OFDM system. The proposed method is based on sparse decomposition and l1-norm optimization algorithm of the received signal over an over-complete matrix composed of both sine and cosine waveforms and time-shifted impulse waveforms. By proper construction of the over-complete matrix, the impulse removal and symbol decoding have been performed simultaneously. Thus, it can reduce the computational complexity. Our method does not require any assumption about the location and magnitude of the impulse and does not demand pilot symbols or null subcarriers unlike other existing methods. Thus, the proposed method is blind in nature. The method is evaluated using different levels of impulse noise and signal-to-noise ratios varying from 0 to 20 dB. Preliminary evaluation results demonstrate the effectiveness of the sparse representation with the proposed dictionaries in effectively removing the impulse noise and improving the bit error rate under different noise levels. © 2017, Springer Science+Business Media New York.

Circuits, Systems, and Signal Processing

Blind Impulse Estimation and Removal Using Sparse Signal Decomposition Framework for OFDM Systems

In this paper, the authors present an automated method for quality assessment of electrocardiogram (ECG) signal. Our proposed method not only detects and classifies the ECG noises but also localizes the ECG noises which can play a crucial role in extracting reliable clinical features for ECG analysis systems. The proposed method is based on three stages: Wavelet decomposition of ECG signal into sub-bands; simultaneous ECG signal and noise reconstruction; extraction of temporal features such as maximum absolute amplitude, zerocrossings, kurtosis and autocorrelation function for detection, localization and classification of ECG noises including flat line (FL), time-varying noise or pause (TVN), baseline wander (BW), abrupt change (AB), power line interference (PLI), muscle artifacts (MA) and additive white Gaussian noise (AWGN). The proposed method is tested and validated against manually annotated ECG signals corrupted with aforementioned noises taken from MIT-BIH arrhythmia database, Physionet challenge database, and real-time recorded ECG signals. Comparative detection and classification results depict the superior performance of the proposed method over state of art methods. Detection results show that our method can achieve an average sensitivity (Se), average specificity (Sp) and accuracy (A) of 99.61%, 98.51%, 99.49% respectively. Also, the method achieves a Se of 98.18%, and Sp of 94.97% for real-time recorded ECG signals. The method has an average timing error of 0.14 s in localizing the noise segments. Further, classification results demonstrate that the proposed method achieves an average sensitivity (Se), average positive predictivity (PP) and classification accuracy (Ac) of 98.53%, 98.89%, 97.50% respectively. © 2017 Nalecz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences