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

Zearalenone (ZEN) is an important non-steroidal estrogenic mycotoxin produced by fusarium fungi species. A number of methods based on enzyme-linked immune assays (ELISA) and chromatographic approaches are available for the detection of ZEN. In this research, ZEN conjugated by bovine serum albumin (BSA) was immobilized on the surface of the screen-printed carbon electrode (SPCE) followed by the subsequent addition of anti-zearalenone monoclonal antibody (ZEN-MAb), alkaline phosphatase (ALP)-labeled secondary antibody, and 1-napthyl phosphate (1-NP) as a substrate. This immunosensor had good specificity, selectivity, reproducibility, and sensitivity for ZEN (LOD of 0.25 ng mL−1) when employed for quantification based on differential pulse voltammetry (DPV). This immunosensor yielded good recovery values in the range of 89–97% against real matrices (i.e., beer and wine samples) after spiking. This novel immunosensing principle can be extensively applied for the development of advanced sensing techniques for various analytes. © 2018

Department of Chemistry

World University root node

Journal of Electroanalytical Chemistry

A highly sensitive electrochemical immunosensor for zearalenone using screen-printed disposable electrodes

Aflatoxin B1 (AFB1) is the most toxic contaminant, causes carcinogenic, and immune toxic effects. There is an immense need to develop inexpensive, reliable biosensors for AFB1. The electrochemical aptasensor for detection of aflatoxin B1 has received much attention due to their trustworthy procedure. In this work, we have designed an electrochemical aptasensor by using methylene blue (MB) as a signalling fragment and polythiophene-3-carboxylic acid (PT3C) as the signal-enlarging platform. The (PT3C) was first screened onto the screen printed carbon electrode (SPCE) interface, and then the MB-tagged aptamer was immobilized on SPCE by using hexamethylenediamine (HMDA) as a spacer via carbodiimide amide-bonding chemistry. AFB1 has been chosen as model analyte to test the proposed aptasensing platform. A good dynamic range 2.5–30 ng L−1 was obtained for AFB1 with a limit of detection (LOD 1.6 ng L−1). The good reproducibility was recorded with RSD% of 3.21. The obtained straight-line equation was 3.6099 x + 19.073, R2 = 0.9977. For real-world sample applications, this aptasensor has been used in coffee samples. It displayed good recovery in the range 88.2–93.3%, thus showed the effectiveness of the proposed aptasensor for coffee samples. © 2019

Sensing and Bio-Sensing Research

An electrochemical aptasensor based on polythiophene-3-carboxylic acid assisted methylene blue for aflatoxin B1 detection

Zero shot learning (ZSL) aims to recognize unseen classes by exploiting semantic relationships between seen and unseen classes. Two major problems faced by ZSL algorithms are the hubness problem and the bias towards the seen classes. Existing ZSL methods focus on only one of these problems in the conventional and generalized ZSL setting. In this work, we propose a novel approach, Semantically Aligned Bias Reducing (SABR) ZSL, which focuses on solving both the problems. It overcomes the hubness problem by learning a latent space that preserves the semantic relationship between the labels while encoding the discriminating information about the classes. Further, we also propose ways to reduce bias of the seen classes through a simple cross-validation process in the inductive setting and a novel weak transfer constraint in the transductive setting. Extensive experiments on three benchmark datasets suggest that the proposed model significantly outperforms existing state-of-the-art algorithms by $\sim$1.5-9% in the conventional ZSL setting and by $\sim$2-14% in the generalized ZSL for both the inductive and transductive settings.

Department of Data Science

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Semantically aligned bias reducing zero shot learning

Conventional machining processes face several problems pertaining to the use of cutting fluids since most of them are toxic and contribute to a major portion of overhead costs. To address these issues, several methods like usage of solid lubricants, surface treatment, coating, minimum quantity lubrication and texturing of cutting tools have been adopted. Micro-texturing on cutting tool is a relatively recent technique which is being used to improve the tribological characteristics of the tool surface. Typical methods available for surface texturing are chemical etching, electro chemical machining, laser beam machining and electric discharge machining. Amongs these methods, there is a significant lack of literature exploring the feasibility of electric discharge machining (EDM) as a texturing process, especially on commonly used tool materials such as high-speed steel. This paper investigates the fabrication of micro-textures on high-speed steel to use micro-EDM. The EDM process parameters were optimized to create uniform textures. Upon comparing the performance of the textured cutting tools with conventional tools, it was found that the current texture geometry was highly effective in reducing the cutting forces at low speeds. © 2019, The Brazilian Society of Mechanical Sciences and Engineering.

Department of Mechanical Engineering

Journal of the Brazilian Society of Mechanical Sciences and Engineering

Electric discharge texturing of HSS cutting tool and its performance in dry machining of aerospace alloy

The requirements of microfeature-based systems are essentially increasing due to their usage in every major field. Market needs microproducts with more functionality, information processing ability integrated together with compact size. Electro-discharge deposition process is an emerging nonlithographic, additive process to manufacture high aspect ratio 3D microfeatures. The current research work develops and investigates the application of magnetic field and shielding gas in the electro-discharge deposition process with experimental work and simulation model. Response surface methodology model is developed to perform parametric analysis and to ascertain the significance of introducing magnetic field and shielding gas in an electro-discharge deposition process. Results from atomic force microscope and optical image microscope shows that at higher magnetic field the deposition height increases with reduced width. From the EDAX compositional analysis, it is noted that the presence of shielding gas increases the percentage of copper composition and reduces the carbon and oxygen composition in the deposited material. The obtained results confirmed that the presence of magnetic field and shielding gas significantly improves the deposition process. © IMechE 2018.

Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science

Investigation of magnetic field and shielding gas in electro-discharge deposition process

Transfer learning algorithms utilize knowledge from a data-rich source domain to learn a model in the target domain where labeled data is scarce. This paper presents a novel solution for the challenging and interesting problem of Heterogeneous Transfer Learning (HTL) where the source and target task have heterogeneous feature and label spaces. Contrary to common space based HTL algorithms, the proposed HTL algorithm adapts source data for the target task. The correspondence required for aligning the heterogeneous features of the source and target domain is obtained through labels across two domains that are semantically aligned using web-induced knowledge. The experimental results suggest that the proposed algorithm performs significantly better than state-of-the-art transfer approaches on three diverse real-world transfer tasks.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Web-induced heterogeneous transfer learning with sample selection

The ability of proteins to sense and/or generate membrane curvature is crucial for many biological processes inside the cell. We introduce a model for the binding and unbinding of curvature inducing proteins on vesicles using Dynamic Triangulation Monte Carlo (DTMC) simulations. In our study, the interaction between membrane curvature and protein binding is characterised by the binding affinity parameter μ, which indicates the interaction strength. We demonstrate that both sensing and generation of curvature can be observed in the same system as a function of the protein binding affinity on the membrane. Our results show that at low μ values, proteins only sense membrane curvature, whereas at high μ values, they induce curvature. The transition between sensing and generation regimes is marked by a sharp change in the μ-dependence of the protein bound fraction. We present ways to quantitatively characterise these two regimes. We also observe that imposing tension on the membrane (through internal excess pressure for liposomes) extends the region of curvature sensing in the parameter space. © 2019 The Royal Society of Chemistry.

Soft Matter

Transition from curvature sensing to generation in a vesicle driven by protein binding strength and membrane tension

Sugarcane and rice are cultivated in vast tracts of land in the southern part of India. The bagasse and rice husk that are collected during the processing of sugarcane and rice paddies, respectively, possess good calorific values and are used for supplementary energy production. However, the ash generated in the process is dumped in landfills. This paper evaluates the benefits of using these agro-waste ashes (sugarcane bagasse ash (SCBA) and rice husk ash (RHA)) as cement replacement in concrete, through a systematic investigation of strength and durability characteristics of two different strength grades of concrete. The results indicate that the compressive strength of bagasse-ash- and RHA-blended concretes was higher than that of control ordinary Portland cement (OPC) specimens for both grades of concrete. In addition to improved strength, remarkable resistance against water and air and chloride permeability was observed for the blended cement concrete specimens. In the same way, SCBA- and RHA-blended mortar specimens performed better against sulfate attack compared to control OPC specimens. The paper also evaluates the sustainability impact of the concretes produced using SCBA and RHA and the results from this study clearly show that these materials provide a local approach to the production of sustainable concrete. © 2019 ICE Publishing: All rights reserved.

Department of Civil Engineering

Green Materials

Durability of concrete with agro-waste: A local approach to sustainability

The use of nanotechnology is of prominent research interest in the construction industry. Introducing nanomaterials into cementitious systems enhances its characteristic material properties. Nano-silica is the most efficient nanomaterial in replacing cement without compromising its strength and durability. Nano-silica also enhances the properties of cement when in conjugation with other supplementary cementitious materials. Nano-silica offers high chemical reactivity and introduces filler effect in the cement matrix, thereby densifying the interfacial transition zone (ITZ) and improving the properties of cement-based materials. However, the addition of nano-silica more than the optimum dosage reduces the strength and durability. Apart from the dosage, many other parameters also influence the properties of nano-slica blended cement composites. This study deals with the changes in characteristic properties of cement and cement-based materials upon incorporation of nano-silica. © Springer Nature Singapore Pte Ltd. 2019.

Lecture Notes in Civil Engineering

Influence of nano-silica on characteristics of cement mortar and concrete

Continuous periodical monitoring of clopidogrel in physiological body fluids is indispensable in medical diagnosis of heart ailments and cardiovascular diseases. A highly sensitive electrochemical sensor has been fabricated with silver nanoparticles embedded chitosan-carbon nanotube hybrid composite (AgChit-CNT) as sensor interface for detection of the important anti-platelet drug, clopidogrel (CLP). Synthesized AgChit-CNT nanocomposite is examined by x-ray diffraction, Raman spectroscopy and field emission scanning electron microscopy for its chemical and structural characteristics. Crystalline silver nanoparticles of about 35 nm are well distributed in the composite and have formed continuous chain like linkages with CNTs all throughout. Electrochemical responses of the fabricated AgChit-CNT nanocomposite electrode for the determination of CLP have been examined by cyclic voltammetry and electrochemical impedance spectroscopy. The nanoAg patterned CNT nanocomposite interface acts as an excellent electron transfer mediator towards the oxidation of clopidogrel. Electrochemical determination of CLP was investigated by differential pulse voltammetry (DPV) and amperometric analysis under optimized conditions. The limit of detection by DPV and amperometry were 30 nM and 10 nM, respectively, and the time of the analysis is as low as 10 s. Practical applicability for determination in artificially prepared urine and pharmaceutical formulation has been examined with good recovery limits of 95.2 to 102.6%. © 2019