Motilal Nehru National Institute of Technology Allahabad

About: Motilal Nehru National Institute of Technology Allahabad is a education organization based out in Allahabad, Uttar Pradesh, India. It is known for research contribution in the topics: Computer science & Control theory. The organization has 2475 authors who have published 5067 publications receiving 61891 citations. The organization is also known as: NIT Allahabad & Motilal Nehru Regional Engineering College.

Bienzyme-Functionalized Monodispersed Biocompatible Cuprous Oxide/Chitosan Nanocomposite Platform for Biomedical Application

Abstract: The ultrafine monodispersed cuprous oxide (Ufm-Cu(2)O) nanoparticles have been successfully synthesized by a facile wet chemical method using poly-N-vinylpyrrolidone (PVP) as a capping agent. This colloidal solution of Ufm-Cu(2)O and chitosan (CS) is electrophoretically deposited (EPD) onto the indium tin-oxide (ITO) glass substrate. Thus synthesized nanocomposite has been characterized by X-ray powder diffraction (XRD, ∼6 nm), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and Fourier transform infrared (FTIR) spectroscopic techniques. This novel biomedical nanocomposite platform has been explored to fabricate a cholesterol biosensor by immobilizing cholesterol esterase (ChEt) and cholesterol oxidase (ChOx) onto Ufm-Cu(2)O-CS/ITO electrode surface. The seed germination tests of these biomaterials (Ufm-Cu(2)O-CS nanocomposite and ChOx-ChEtUfm-CuO(2)-CS nanobiocomposite), conducted using the disc diffusion method, reveal strong activity against the common pathogens and crops, indicating biocompatibility of the nanocomposite. Under optimized conditions, the linearity between the current response and the cholesterol concentration has been obtained in the range of 10-450 mg/dL, with detection limit of 15.9 mg/dL cm(-2) and a high sensitivity of 0.895 μA/(mg/dL cm(-2)). The proposed biocompatible ChEt-ChOx/Ufm-Cu(2)O-CS/ITO bioelectrode shows fast response time (<5 s), good reproducibility, and long-term stability. This biocompatible biosensor has been used to determine the total cholesterol levels in human serum samples. Investigated antimicrobial activities of bienzyme-functionalized Ufm-Cu(2)O-CS nanocomposite are the potential platform for biomedical applications.

Recent advancements in lateral flow immunoassays: A journey for toxin detection in food.

Abstract: Biotechnology embraces various physical and chemical phenomena toward advancement of health diagnostics. Toward such advancement, detection of toxins plays an important role. Toxins produce severe health impacts on consumption with high mortality associated in acute cases. The most prominent route of infection and intoxication is through food matrices. Therefore, rapid detection of toxins at low concentrations is the need of modern diagnostics. Lateral flow immunoassays are one of the emergent and popularly used rapid detection technology developed for detecting various kinds of analytes. This review thus focuses on recent advancements in lateral flow immunoassays for detecting different toxins in agricultural food. Appropriate emphasis was given on how the labels, recognition elements, or detection strategy has laid an impact on improvement in immunochromatographic assays for toxins. The paper also discusses the gradual change in sensitivities and specificities of assays in accordance with the method of food processing used. The review concludes with the major challenges faced by this technology and provides an outlook and insight of ideas to improve it in the future.

Portfolio optimization using novel co-variance guided Artificial Bee Colony algorithm

Abstract: Although the use of evolutionary algorithms and fuzzy logic for portfolio optimization is an established research area, this field remains fascinating because of its important financial aspects. The field is brisk and it trances as there always remain research issues which are yet to explore. The problem of portfolio optimization comprises of finding an optimal distribution of funds among various available securities so as to maximize the return and minimize the risk. Artificial Bee Colony (ABC) is one of the effectual and widely used optimization technique based on swarm intelligence. Mixing co-variance principles with ABC algorithm assists in quick convergence with more precision. This paper presents a novel co-variance guided Artificial Bee Colony algorithm for portfolio optimization. As portfolio optimization consists of simultaneous optimization of multiple conflicting objectives, this algorithm is named as Multi-objective Co-variance based ABC (M-CABC). The efficacy of the proposed algorithm is tested on benchmark problems of portfolio optimization from the OR-library. The results validate the adept performance of the proposed algorithm in finding various optimal trade-off solutions simultaneously handling realistic constraints. The article concludes with exhaustive post-result analysis and observatory remarks to bring out some of the crucial properties of optimal portfolios.

Leveraging multimodal information for event summarization and concept-level sentiment analysis

Abstract: The rapid growth in the amount of user-generated content (UGCs) online necessitates for social media companies to automatically extract knowledge structures (concepts) from photos and videos to provide diverse multimedia-related services. However, real-world photos and videos are complex and noisy, and extracting semantics and sentics from the multimedia content alone is a very difficult task because suitable concepts may be exhibited in different representations. Hence, it is desirable to analyze UGCs from multiple modalities for a better understanding. To this end, we first present the EventBuilder system that deals with semantics understanding and automatically generates a multimedia summary for a given event in real-time by leveraging different social media such as Wikipedia and Flickr. Subsequently, we present the EventSensor system that aims to address sentics understanding and produces a multimedia summary for a given mood. It extracts concepts and mood tags from visual content and textual metadata of UGCs, and exploits them in supporting several significant multimedia-related services such as a musical multimedia summary. Moreover, EventSensor supports sentics-based event summarization by leveraging EventBuilder as its semantics engine component. Experimental results confirm that both EventBuilder and EventSensor outperform their baselines and efficiently summarize knowledge structures on the YFCC100M dataset.