Showing papers by "Jawaharlal Nehru Technological University, Hyderabad published in 2021"

A Comparative Review of Natural and Synthetic Biopolymer Composite Scaffolds.

Abstract: Tissue engineering (TE) and regenerative medicine integrate information and technology from various fields to restore/replace tissues and damaged organs for medical treatments. To achieve this, scaffolds act as delivery vectors or as cellular systems for drugs and cells; thereby, cellular material is able to colonize host cells sufficiently to meet up the requirements of regeneration and repair. This process is multi-stage and requires the development of various components to create the desired neo-tissue or organ. In several current TE strategies, biomaterials are essential components. While several polymers are established for their use as biomaterials, careful consideration of the cellular environment and interactions needed is required in selecting a polymer for a given application. Depending on this, scaffold materials can be of natural or synthetic origin, degradable or nondegradable. In this review, an overview of various natural and synthetic polymers and their possible composite scaffolds with their physicochemical properties including biocompatibility, biodegradability, morphology, mechanical strength, pore size, and porosity are discussed. The scaffolds fabrication techniques and a few commercially available biopolymers are also tabulated.

Carbon dioxide adsorption based on porous materials

Abstract: Global warming due to the high concentration of anthropogenic CO2 in the atmosphere is considered one of the world's leading challenges in the 21st century as it leads to severe consequences such as climate change, extreme weather events, ocean warming, sea-level rise, declining Arctic sea ice, and the acidification of oceans This encouraged advancing technologies that sequester carbon dioxide from the atmosphere or capture those emitted before entering the carbon cycle Recently, CO2 capture, utilizing porous materials was established as a very favorable route, which has drawn extreme interest from scientists and engineers due to their advantages over the absorption approach In this review, we summarize developments in porous adsorbents for CO2 capture with emphasis on recent studies Highly efficient porous adsorption materials including metal–organic frameworks (MOFs), zeolites, mesoporous silica, clay, porous carbons, porous organic polymers (POP), and metal oxides (MO) are discussed Besides, advanced strategies employed to increase the performance of CO2 adsorption capacity to overcome their drawbacks have been discoursed

Effects of soret, dufour, hall current and rotation on MHD natural convective heat and mass transfer flow past an accelerated vertical plate through a porous medium

Abstract: This article concentrates on the impact of Hall current, Radiation, Soret, and Dufour on an unsteady MHD Natural convective flow over an infinite vertical plate fixed in a porous media. The entire system is supposed to revolve with an unvarying angular velocity Ω′around the perpendicular to the plate and an unvarying transverse magnetic field is enforced along the normal to the plate which is coordinated in the fluid area. The solution of the non-deimensional governing equations along with the boundary conditions are solved by using effeicient Galerkin Method. The effect of different pertinent flow parameters on velocity, temperature, and concentration distributions and the numerical outcomes are examined and revealed graphically. With the increase of Sorent number the concentration profile increases and reverse trend is observed in the case of Dufour numbers. Comparision done with the recent work on exceptional instances of the problem is acquired and is seen to be in accord.

Investigation on the mechanical, tribological, morphological and machinability behavior of stir-casted Al/SiC/Mo reinforced MMCs

Abstract: Aluminum matrix composites (AMCs), reinforced with SiC and Mo, are formulated using stir casting. The influence of SiC and Mo inclusions on microstructural behavior, and machinability of composites was investigated. Microstructural behavior is analyzed using scanning electron microscopy (SEM), X-ray diffraction (XRD) and energy dispersive spectroscopy (EDS) in the form of microhardness, tensile strength, wear behavior, density, and porosity as per ASTM standards. SEM and EDS confirm the existence and dispersion of SiC and Mo particulates in the matrix grain structure. XRD patterns indicate Al5Mo and Al12Mo compounds formation in hybrid composites, but with the least intensity. Optical microscopy imagery confirms dendritic structure formation with the inclusion of SiC and Mo particulates in the base matrix. Machined surface roughness was influenced by speed-feed while tool wear by all inputs.

Impact of Alkali Treatment on Characterization of Tapsi (Sterculia Urens) Natural Bark Fiber Reinforced Polymer Composites

Abstract: Nowadays, research attention on composite materials accentuates where not only was their unique attributes agglomerated-alleviated weight and density, elevated impact and specific strengths, but al...

Journey of anthraquinones as anticancer agents – a systematic review of recent literature

Abstract: Anthraquinones are privileged chemical scaffolds that have been used for centuries in various therapeutic applications. The anthraquinone moiety forms the core of various anticancer agents. However, the emergence of drug-resistant cancers warrants the development of new anticancer agents. The research endeavours towards new anthraquinone-based compounds are increasing rapidly in recent years. They are used as a core chemical template to achieve structural modifications, resulting in the development of new anthraquinone-based compounds as promising anticancer agents. Mechanistically, most of the anthraquinone-based compounds inhibit cancer progression by targeting essential cellular proteins. Herein, we review new anthraquinone analogues that have been developed in recent years as anticancer agents. This includes a systematic review of the recent literature (2005–2021) on anthraquinone-based compounds in cell-based models and key target proteins such as kinases, topoisomerases, telomerases, matrix metalloproteinases and G-quadruplexes involved in the viability of cancer cells. In addition to this, the developments in PEG-based delivery of anthraquinones and the toxicity aspects of anthraquinone derivatives are also discussed. The review dispenses a compact background knowledge to understanding anthraquinones for future research on the expansion of anticancer therapeutics.

Quantification of flood mitigation services by urban green spaces using InVEST model: a case study of Hyderabad city, India

Abstract: Urban floods have become more frequent across the globe. The transformation of the urban landscape with increased concretization and dwindling green cover has resulted in excess run-off generation thereby causing the flash floods. The protective role and ecosystem benefits of urban green spaces needs to be quantified so that it will unlock the possibilities of integrating natural capital thinking into policymaking. Hence in this study, we quantified the flood mitigation service of green spaces and estimated the tangible economic damage to the built infrastructure in the Hyderabad metropolitan city, India using the Integrated Valuation of Ecosystem Services and Trade-offs model. The analysis was carried out for 2-years and 5-years design precipitation of 1 h duration. Results show that 44–50% of the precipitation is retained by the urban green and open spaces. With an increase of 13% in the rainfall intensity (from 2-years to 5-years), the run-off volume has increased by 21%, while the run-off retained has increased only by 5%, which indicates that even slight increase in rainfall intensity results in huge run-off generation that causes commensurate economic damages. The economic damage due to flood inundation of the built infrastructure is estimated to be 1.39 million USD using the unit cost method. Overall, the indicator of run-off retention service is quantified as 4.25E + 13 and 4.46E + 13 for the 2-years and 5-years return period precipitation, respectively. The structural and non-structural flood mitigation measures are also enumerated along with the limitations of the model.

Ohmic heating and chemical reaction effect on MHD flow of micropolar fluid past a stretching surface

Abstract: The current article discuss the interaction between the Ohmic heating and chemical reaction impact on MHD micropolar fluid flow past a stretching surface in the existence of chemical reaction using Runge–Kutta–Fehlberg method (RKF-45) along with the shooting procedure. By applying some similarity transformations, the governing equations were changed to ODEs. Numerical consequences were calculated for many values of pertinent factors on flow, angular velocity, thermal, mass transfer are exposed graphically and the numerical outcomes of the skin friction, couple stress at the wall, Nusselt number, Sherwood number are entered in tabulated form. With an increase of the material parameter, the velocity, couple stress, Sherwood number, Nusselt number, and temperature, concentration, and shear stress increase, while temperature, concentration, and shear stress decreases.

Effect of infill pattern, density and material type of 3D printed cubic structure under quasi-static loading:

Abstract: The present research work is aimed to investigate the effect of infill pattern, density and material types of 3D printed cubes under quasi-static axial compressive loading. The proposed samples wer...

An optimized SVM based possibilistic fuzzy c-means clustering algorithm for tumor segmentation

Abstract: To design an efficient partial differential equation-based total variation method for denoising and possibilistic fuzzy c-means clustering algorithm for segmentation and these methods presented the more detailed information of the MRI medical images compared to traditional methods. In this article, the pipeline of the proposed method described by two modules like pre-processing and segmentation. In pre-processing, noisy image is decomposed using nonsubsampled contourlet transform and it contains highpass contourlet coefficient (i.e., noisy coefficient) is removed by the threshold method as well. After reconstruction, the primary denoised image is enhanced by an improved partial differential equation-based total variation method in terms of image details like edges, boundaries, etc. In segmentation, the enhanced primary denoised image is segmented by an improved possibilistic fuzzy c-means clustering algorithm that avoids limitations in possibilistic c-means, fuzzy c-means, and K-means clustering. Next, a support vector machine classifier is utilized to identify brain tissues into gray matter, white matter, cerebrospinal fluid, and tumor part. The parameters were optimally selected by a grey wolf optimization algorithm for the classification of brain tissues. The performance of the proposed method is computed with reference to peak signal-to-noise ratio, mean square error, structural similarity index, sensitivity, specificity, and accuracy. The experimental results claimed that the proposed method is better than the traditional methods.

An automated essay scoring systems: a systematic literature review

Abstract: Assessment in the Education system plays a significant role in judging student performance. The present evaluation system is through human assessment. As the number of teachers' student ratio is gradually increasing, the manual evaluation process becomes complicated. The drawback of manual evaluation is that it is time-consuming, lacks reliability, and many more. This connection online examination system evolved as an alternative tool for pen and paper-based methods. Present Computer-based evaluation system works only for multiple-choice questions, but there is no proper evaluation system for grading essays and short answers. Many researchers are working on automated essay grading and short answer scoring for the last few decades, but assessing an essay by considering all parameters like the relevance of the content to the prompt, development of ideas, Cohesion, and Coherence is a big challenge till now. Few researchers focused on Content-based evaluation, while many of them addressed style-based assessment. This paper provides a systematic literature review on automated essay scoring systems. We studied the Artificial Intelligence and Machine Learning techniques used to evaluate automatic essay scoring and analyzed the limitations of the current studies and research trends. We observed that the essay evaluation is not done based on the relevance of the content and coherence.

Experimental determination of thermophysical properties of Indonesian fly-ash nanofluid for heat transfer applications

Abstract: The heat transfer fluid's thermal properties are a significant topic of current research. In this study, coal fly ash nanoparticles of 14 nm average diameter were dispersed in water to prepare stab...

Improved partial differential equation-based total variation approach to non-subsampled contourlet transform for medical image denoising

Abstract: This article proposes an improved partial differential equation (PDE)-based total variation (TV) model that enhances grey and coloured brain tumour images obtained by magnetic resonance imaging. A nonsubsampled contourlet transform was applied to images from standard databases that converted into lowpass and highpass (or bandpass) contourlet coefficients. An improved version of the power-law transform method was used on the lowpass contourlet coefficients, and an adaptive threshold method was applied to the highpass (or bandpass) contourlet coefficients. The inverse contourlet transform was performed on all the enhanced contourlet coefficients to generate a complete brain tumour image. Finally, the PDE-based TV model was applied to this image to produce the denoised image. The performance of the suggested method was calculated in terms of the peak signal-to-noise ratio, mean square error, and structural similarity index. This method achieved the best peak signal-to-noise ratio, mean square error, and structural similarity index of 77.9846 dB, 0.00012612, and 97.895%, respectively, compared to the conventional PDE+modified transform-based gamma correction, adaptive PDE+generalized cross-validation, parallel magnetic resonance imaging, and Berkeley wavelet transform+support vector machine methods.

Experimental investigation on thermal conductivity of fly ash nanofluid and fly ash-Cu hybrid nanofluid: prediction and optimization via ANN and MGGP model

Abstract: In the present work, the thermal conductivity (TC) of stable water base fly ash and fly ash-Copper (80:20 vol.%) nanofluid was determined experimentally in the temperature range of 30–60 °C for the...