Pondicherry University
  • Puducherry, Pudhucherry, India
Recent publications
Further, modification has been made to the tapering part of the SIW structure to form an elemental resonating antenna, capable of generating wavelengths of 28 and 38 GHz, for use with the SIW frame structure. Allow the tapering portion to flare out as much as possible, until it intersects with the intersecting branch at either side, and as a final step, inset bends should cover both of the vias on either end. This structural change boosts the gain, efficiency, and bandwidth significantly. By using 28 GHz as a design frequency, the chip will have an efficiency of 96.19% and a bandwidth of 0.932 GHz. Antenna gain is 7.12 dB and the bandwidth is 0.550 GHz at 38 GHz. This antenna has a gain of 9.04 dB. In some ways, its design resembles those seen in literature, as well as fulfilling the expectations of future wireless technologies. To ensure that all parties in the transaction have access to all information, the sent information is not encrypted or is delivered unencrypted. CST Studio Suite was used to simulate the simulation prediction.
This study aims to elucidate the effect of Multi-Stage HTL with a constant resident time of 30 min for three different feedstocks including kitchen wastewater sludge (KwWs), freshwater microalgae Chlorella sorokiniana (UUIND6), Co-HTL (KwWs + UUIND6) to obtain the maximum bio-oil yield. According to the results obtained, KwWs appears to be the most suitable for conversion into energy-dense bio-oil under a sustainable biorefinery approach for increased bio-oil yields i.e., 72.75 ± 0.37 wt%, with HHV of 40.52 MJ/kg and energy recovery of 53.64 wt%. Further, the bio-oils and bio-chars derived from different types of biomasses obtained at different temperature conditions were analyzed by GC–MS, NMR, FTIR, and Raman spectroscopy to identify variations in the bio-crude compounds.
Cancer is the most frequent and deadly disease, with an increasing number of cancer patients and deaths. Breast cancer is becoming the most common type of cancer among women. This paper describes an octagonal‐shaped ultrawide band patch antenna with a denim substrate having a dielectric constant of 1.7. Various positions of the tumor inside the breast phantom are analyzed by the designed antenna using computer simulation technology (CST) Microwave Studio. Multiple tumors are traced by specific absorption rate analysis. The frequency range covered by the antenna is 2.4–10.1 GHz.
Taylor column phenomenon is a highly interesting flow-feature which is the result of Coriolis and inertia forces and can play a crucial role in modulating heat transfer characteristics. However, there is not much progress to capture Taylor column phenomenon numerically, let alone to study its heat transfer characteristics. In this regard, we have investigated the translation of a uniformly heated sphere through a rotating incompressible viscous fluid. The associated energy equation in axially symmetric spherical polar co-ordinates is solved using the Higher-Order Compact Scheme (HOCS) of the order four for steady high Reynolds number (Re) flow. It is noticed that the presence of Taylor column delays the rate of heat transfer past the sphere in the upstream zone while enhancing it in the downstream zone. The presence of the Taylor column at higher values of inverse Rossby number (1/Ro) modifies heat transfer in a typical manner over the cross-section of the sphere. A comparative study made between low Re heat transfer and steady high Re heat transfer unveils a broad perspective into the flow-physics of the problem.
This review paper reports the detailed assessment of biofuel (bio-oil and biodiesel) production capabilities and the potential utilization of Azolla macroalgae in bioremediation and biofertilizer applications. Biodiesel and its blends were utilized in the transportation sector to minimize fossil fuel emissions and greenhouse gas (GHG). Another significant biofuel is bio-oil, which is produced by pyrolysis of biomasses. High energy density combined with easiness of storage and transportation of bio-oil compared to gaseous products, bio-oil is considered a possible source to replace petroleum fuel for power production. The key reason for choosing Azolla species as feedstock for biofuel production is its sustainability, high lipid and energy content. Besides, the Azolla grows in simple wetlands and wastewater, which is efficient and cost-effective. The results from the various literature ensured that the Azolla based biofuels are a better alternative to fossil fuels. The wastewater from the industries and nuclear power plants contains pollutants such as heavy metals and metalloids. Heavy metals cause several damage to the ecosystem. The conventional methods of treating wastewater are expensive and time-consuming, whereas the bioremediation method provides low-cost alternate methods. The removal of heavy metals from wastewater is achieved using Azolla algae, a biological source present in ditches and ponds. Azolla quickly spreads as a dense layer over the water surface and adsorbed heavy metals from the wastewater. The current study critically reviewed the Azolla’s potential capacity to be used in the phytoremediation method and remove the heavy metals from wastewater to better environmental conditions. In addition, Azolla is reported as a bio-fertilizer and green manure in gardens and rice fields due to their high cellulosic content.
A NASICON based phosphate glass systems (Li(1-x)Nax)5TiP3O12 with various composition x = 0, 0.2, 0.4, 0.6, 0.8 and 1.0 were synthesized by melt quenching method. X-ray diffraction patterns substantiate the amorphous nature. The mixed alkali effect (MAE) was explicated in thermal studies as well as in dielectric spectroscopy. The thermal analysis demonstrates that the series exhibit a MAE in their characteristic thermal parameters also. The dynamics of the ions in mixed alkali glass illustrate miniaturization of dc conductivity and maximum in their respective activation energy at x = 0.6. This decrease in conductivity in the glass composition is observed in all temperature range 273 K to 473 K and follows the same manner as glass transition temperature. The frequency dependence ac conductivity, as well as the electric modulus espouse a few interesting aspects of scaling regarding MAE.
The biosynthesis of nanoparticles (NPs) has gained an overwhelming interest due to their biological applications. However, NPs synthesis by pigmented extreme halophiles remains underexplored. The NPs synthesis using pigmented halophiles is inexpensive and less toxic than other processes. In this study, pigmented halophilic microorganisms (n = 77) were screened to synthesize silver chloride nanoparticles (AgCl-NPs) with silver nitrate as metal precursors, and their biological applications were assessed. The synthesis of AgCl-NPs was possible using the crude extract from cellular lysis (CECL) of six extreme halophiles. Two of the AgCl-NPs viz. AK2-NPs and MY6-NPs synthesized by the CECL of Haloferax alexandrinus RK_AK2 and Haloferax lucentense RK_MY6, respectively, exhibited antimicrobial, antioxidative, and anti-inflammatory activities. The surface plasmon resonance of the AgCl-NPs was determined with UV spectroscopy. XRD analysis of AK2-NPs and MY6-NPs confirmed the presence of silver in the form of chlorargyrite (silver chloride) having a cubic structure. The crystallite size of AK2-NPs and MY6-NPs, estimated with the Scherrer formula, was 115.81 nm and 137.50 nm. FTIR analysis verified the presence of diverse functional groups. Dynamic light-scattering analysis confirmed that the average size distribution of NPs was 71.02 nm and 117.36 nm for AK2-NPs and MY6-NPs, respectively, with monodisperse nature. The functional group in 1623–1641 cm⁻¹ indicated the presence of protein β-sheet structure and shifting of amino and hydroxyl groups from the pigmented CECL, which helps in capping and stabilizing nanoparticles. The study provides evidence that CECL of Haloferax species can rapidly synthesize NPs with unique characteristics and biological applications.
The consumer market has significantly increased in the search for nutritional and probiotic formulated products. In the present study, probiotic characterization parameters have been evaluated for the bacteria isolated from fermented millet porridge or ragi koozh and jalebi batter. Initially, 30 colonies were randomly picked and screened for lactic acid production. Lactic acid-producing 13 isolates showing gram-positive cell wall, non-spore-forming capacity and catalase-negative strains were subjected to probiotic characterization. Among 13 isolates, 2 isolates S9 and S13 exhibited good tolerance towards in-vitro characterization parameters such as acid and bile tolerance, adhesion to hydrocarbons, autoaggregation, co-aggregation, antibacterial activity, and safety measures. The potential probiotic strains S9 and S13 were identified by molecular methods, and evolutionary imprints and submitted to GenBank as Weisella cibaria and Enterococcus lactis. Results showed the efficacy of probiotic characteristics of isolates S9 and S13 which can be used for the formulation of probiotic products.
In this paper, a modified version of the Gravitational Search Algorithm (GSA) based on levy flight and chaos theory namely LCGSA has been used to train Multilayer Perceptron (MLP) neural network for feature classification and function approximation. In LCGSA, the diversification of the search space is carried out by levy flight while chaotic maps have been utilized for the intensification of the candidate solutions towards the global optimum. Besides, the sigmoid function acts as an objective function for LCGSA based MLP pair in order to minimize the neural bias and error. Moreover, the matrix encoding scheme is used for representing the candidate solutions. To verify the effectiveness of LCGSA, it has been applied to three well-known classification datasets namely XOR, Balloon, and Heart. Besides, two function approximation benchmarks including Sigmoid and Cosine functions are also considered for the performance evaluation. Furthermore, the quantitative and qualitative analysis of the simulation results has been carried out. The quantitative performance metrics include statistical measures, run time, mean square error (MSE), and average test error (ATE). Also, the simulation analysis is benchmarked by utilizing various qualitative measures such as convergence rate, box plot analysis, and approximation curves. The signed Wilcoxon rank-sum test is employed to statistically verify the experimental outcomes. In addition, ten LCGSA versions are compared with various hybrid and recent heuristic optimization techniques. The simulation results indicate that LCGSA provides better performance than standard GSA and most of the competing algorithms.
Soil salinity is a leading cause for yield losses in rice, affecting nearly 6% of global rice cultivable area. India is host to a rich diversity of coastal rice landraces that are naturally tolerant to salinity and an untapped source to identify novel determinants of salinity tolerance. In the present study, we have assessed the relative salinity tolerance of 43 previously genotyped rice landraces at seedling stage, using thirteen morpho-physiological and biochemical parameters using a hydroponics system. Among 43 rice varieties, 25 were tolerant, 15 were moderately tolerant, 1 was moderately susceptible and 2 sensitive checks were found to be highly susceptible based on standard salinity scoring methods. In addition to previously known saline tolerant genotypes (Pokkali, FL478 and Nona Bokra), the present study has novel genotypes such as Katrangi, Orkyma, Aduisen 1, Orumundakan 1, Hoogla, and Talmugur 2 as potential sources of salinity tolerance through measurement of morpho-physiological and biochemical parameters including Na+, K+ estimations and Na+/K+ ratios. Further, Pallipuram Pokkali may be an important source of the tissue tolerance trait under salinity. Four marker trait associations (RM455-root Na+; RM161-shoot and root Na+/K+ ratios; RM237-salinity tolerance index) accounted for phenotypic variations in the range of 20.97–39.82%. A significant increase in root endodermal and exodermal suberization was observed in selected rice landraces under salinity. For the first time, variation in the number of suberized sclerenchymatous layers as well as passage cells is reported, in addition to expression level changes in suberin biosynthetic genes (CYP86A2, CYP81B1, CYP86A8 and PERL).
The unprecedented outbreak of the severe acute respiratory syndrome (SARS) Coronavirus-2, across the globe, triggered a worldwide uproar in the search for immediate treatment strategies. With no specific drug and not much data available, alternative approaches such as drug repurposing came to the limelight. To date, extensive research on the repositioning of drugs has led to the identification of numerous drugs against various important protein targets of the coronavirus strains, with hopes of the drugs working against the major variants of concerns (alpha, beta, gamma, delta, omicron) of the virus. Advancements in computational sciences have led to improved scope of repurposing via techniques such as structure-based approaches including molecular docking, molecular dynamic simulations and quantitative structure activity relationships, network-based approaches, and artificial intelligence-based approaches with other core machine and deep learning algorithms. This review highlights the various approaches to repurposing drugs from a computational biological perspective, with various mechanisms of action of the drugs against some of the major protein targets of SARS-CoV-2. Additionally, clinical trials data on potential COVID-19 repurposed drugs are also highlighted with stress on the major SARS-CoV-2 targets and the structural effect of variants on these targets. The interaction modelling of some important repurposed drugs has also been elucidated. Furthermore, the merits and demerits of drug repurposing are also discussed, with a focus on the scope and applications of the latest advancements in repurposing.
Electric vehicles (EVs) are the emerging solution for pollution‐free transportation systems in the modern era. Battery‐operated motor‐powered electric vehicles serve the purpose of transportation with in‐time recharging ability. Routing and traversing locations using EVs demand optimal route selection for retaining delay and power of the vehicle. This manuscript proposes a fitness‐ant colony optimization (FACO)–based route optimization for improving the driving range of EVs. FACO works in two phases: conditional route discovery and range‐sustained traversing to control delay and to deprive EV failures because of earlier power drain. In range‐sustained phase, the fitness of the traversing route is framed by considering the inputs of power and travel time of the EV for ensuring construction of optimal touring paths. The EVs are directed to traverse the paths defined through ACO, after which the available paths are further attuned to identify the most efficient route depending on the braking and battery power of the vehicle. This optimization balances both power and its variants along with travel time for improving the driving range of the EV before it actually drains out. The optimization technique is assessed using arbitrary road and delivery point simulation with real‐time configurations to demonstrate the effectiveness of the proposed method. Experimental results demonstrate the consistency of the proposed FACO by increasing driving distance and delivery point visits. This optimization also achieves lesser power depletion retaining higher charging level with lesser waiting time.
A gene encoding lipase enzyme from Bacillus flexus PU2 was cloned and expressed in E. coli BL21 (DE3) pLysS and purified protein having the molecular weight of 34 kDa. This lipase was found to be alkaline (pH 9) and slightly thermophilic. This lipase was observed to retain its activity in the presence of methanol, ethanol, DMSO, and acetone. Ferrous sulfate, copper sulfate, and manganese sulfate highly enhanced the lipase activity. All the surfactants and detergents were found to inhibit the enzyme activity, whereas the bleaching agent hydrogen peroxide was found to increase the activity. This lipase was observed as a metalloenzyme, and its activity was highly inhibited by EDTA. Also, it is moderately halophilic and can retain the activity between 0.2 and 0.8 M NaCl. Biofilm inhibitory potential of purified lipase was tested against pathogenic Vibrio parahaemolyticus, and the minimal inhibitory concentration observed was 350 U. Different concentration of this enzyme significantly changed the morphology and biofilm density of V. parahaemolyticus and was evinced by SEM and CLSM imaging. The transcriptome levels of genes responsible for biofilm formation, motility, and virulence such as, motX, fliG, and trh were significantly downregulated with lipase treatment.
In the present study, a quaternary Cu-based chalcopyrite semiconductor, Cu2AgIn(S0.5Se0.5)4 (CAISSe) nanoparticles (NPs) was synthesized by a hot injection method. X-ray diffraction (XRD) and Raman spectroscopy studies were carried out to finding the formation of tetragonal crystal structure of synthesized CAISSe NPs. HR-TEM analysis revealed the spherical morphology of the synthesized CAISSe NPs. The charge separation and carrier dynamics of the perovskite with CAISSe NPs deposited on pearl carbon were analyzed by photoluminescence (PL) studies. The intensity of PL spectrum was reduced for CAISSe NPs deposited on pearl carbon than the pristine pearl carbon. By adding sulfur with selenium influences, the device performance was further discussed. A comprehensive analysis of impedance spectroscopy was subsequently carried out to understand the charge transferring nature of perovskite/[email protected] CE interface. The higher PCE (η = 4.64%) is obtained for CAISSe NPs deposited pearl carbon CE based PSC than that of pristine pearl carbon CE based PSC (η = 2.69%).
This framework attempts to introduce a new Distributed denial-of-service (DDoS) attack detection and mitigation model. It is comprised of two stages, namely DDoS attack detection and mitigation. The first stage consists of three important phases like feature extraction, optimal feature selection, and classification. In order to optimally select the features of obtained feature sets, a new improved algorithm is implanted named Improved Update oriented Rider Optimization Algorithm (IU-ROA), which is the modification of the Rider Optimization Algorithm (ROA) algorithm. The optimal features are subjected to classification using the Deep Convolutional Neural Network (CNN) model, in which the presence of network attacks can be detected. The second stage is the mitigation of the attacker node. For this, a bait detection mechanism is launched, which provides the effective mitigation of malicious nodes having Distributed Denial-of-Service (DDoS) attacks. The experimentation is done on the KDD cup 99 dataset and the experimental analysis proves that the proposed model generates a better result which is 90.06% in mitigation analysis and the overall performance analysis of the proposed model on DDoS Attack Detection is 96% better than conventional methods.
Heavy metals (HM) are the major proximate drivers of pollution in the mangrove ecosystem. Therefore, ecological risk (ER) due to HM distribution/concentration in core-sediment of Puzi mangrove region (Taiwan) was examined with tidal influence (TI) along with indigenous rhizospheric bacteria (IRB). The HM concentration was observed higher at active-tidal-sediment compared to partially-active-sediment. Geo-accumulation index (Igeo) and contamination factor (CF) indicated the tidal-sediment was highly contaminated with arsenic (As) and moderately contaminated with Lead (Pb) and Zinc (Zn). However, the pollution loading index (PLI) and degree of contamination (Cd) exhibited ‘no pollution’ and ‘low-moderate degree of contamination’, in the studied region respectively. The isolated IRB (Priestia megaterium, Bacillus safenis, Bacillus aerius, Bacillus subtilis, Bacillus velenzenesis, Bacillus lichenoformis, Kocuria palustris, Enterobacter hormaechei, Pseudomonus fulva, and Paenibacillus favisporus; accession number OM979069-OM979078) exhibited the arsenic resistant behavior with plant-growth-promoting characters (IAA, NH3, and P-solubilization), which can be used in mangrove reforestation and bioremediation of HM.
Magnesium Silicide Stannide [Mg2(Si,Sn)]-based materials are known to be an important class of thermoelectric materials integrating the earth-abundant and non-toxic elements. In this paper, we present the electrical and thermoelectric performances of Mg2−δSi0.35−xSn0.65Gex (x = 0, 0.05 and δ = 0–0.04) alloys. The alloys have been prepared by mechanical alloying along with vacuum hot-pressing technique. The alloys Mg1.96Si0.3Sn0.65Ge0.05 and Mg1.98Si0.3Sn0.65Ge0.05 possess low electrical and thermal conductivity, high Seebeck, and significantly high power factor in comparison to the parent Mg2Si0.35Sn0.65 alloy. The substitution of Ge at the Si site serves two purposes. First, it reduced the bipolar effect due to the enlargement of the band gap and subsequently reduced the lattice thermal conductivity. Furthermore, the creation of Mg vacancy has contributed to the enhancement of phonon scattering at the grain boundaries, which in turn enhanced the Seebeck coefficient, reduced the electrical, and thermal conductivity. The synergetic confluence of improved power factor and low thermal conductivity in Mg1.98Si0.3Sn0.65Ge0.05 resulted in the highest ZT\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathrm{ZT}$$\end{document} value of 0.08 at ~ 523 K, which is ~ 73% higher than the ZT\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ZT$$\end{document} value (~ 0.02) of the parent Mg2Si0.35Sn0.65 alloy.
We report the fabrication and demonstrate the superior performance of robust, cost-effective, and biocompatible hierarchical Au nanoparticles (AuNPs) decorated Ag nanodendrites (AgNDs) on a Silicon platform for trace-level detection of antibiotics (penicillin, kanamycin, and ampicillin) and DNA bases (adenine, cytosine). The hot-spot density dependence studies were explored by varying the AuNPs deposition time. These substrates’ potential and versatility were explored further through the detection of crystal violet, ammonium nitrate, and thiram. The calculated limits of detection for CV, adenine, cytosine, penicillin G, kanamycin, ampicillin, AN, and thiram were 348 pM, 2 nM, 28 nM, 2 nM, 56 nM, 4 nM, 5 nM, and 2 nM, respectively. The analytical enhancement factors were estimated to be ∼10⁷ for CV, ∼10⁶ for the biomolecules, ∼10⁶ for the explosive molecule, and ∼10⁶ for thiram. Furthermore, the stability of these substrates at different time intervals is being reported here with SERS data obtained over 120 days.
The present study is aimed to tailor the structure of zircon (ZrSiO4) for potential application in hard tissue replacements. In this context, zircon (Zr,Ti)1‐x(Dy)x(SiO4)1‐x(PO4)x type solid solution has been formed through a simple sol‐gel technique. Zircon formation is induced by the Ti4+ substitution, while the progressive addition of Dy3+/PO43– led to their accomodation at the resultant lattice sites. The maximum occupancy limit of Dy3+/PO43‐ is determined as 20 wt.% beyond which the ZrSiO4 structure is destabilized to enable the exclusion of Ti4+ and Zr4+ and subsequently yields ZrTiO4 trace alongside the crystallization of DyPO4. Dy3+ accommodation facilitated the improved absorption and emission [blue (483 nm) and yellow (576 nm)] phenomena and further the paramagnetic features are also induced in the resultant ZrSiO4. This article is protected by copyright. All rights reserved
The nanoparticles surface area, intrinsic sites, exposed microcrystal shapes and lattice planes are some of the key factors in nanocatalysis. The influence of nanoparticles shape dependent had been profound effect on its catalytic activity. This study is focused on the synthesis of morphologically shape-controlled silver (Ag) nanoparticles supported on α-Al2O3 catalysts were performed. The correlation of Ag NPs with varied facets and lattice planes on the catalytic activities in chemoselective reduction of nitro compounds was investigated. Engineering the silver nanoparticles with different shapes and facets i.e., nanocubes (AgNCs), nanowires (AgNWs) and nano spheres (AgNSPs) were synthesized by using modified polyol method. It is demonstrated that there is a significant difference in their activities with respect to the shape and nanocrystal facets. The evolution of nanoshapes and the structural properties of Ag nanoparticles were analysed by SEM, TEM, HR-TEM and P-XRD techniques. From XRD, Ag nanocubes exhibited high percentage of low index (100) facets which are favourable active centers than (111) plane in nitro reduction. We observed that the silver nanocubes selectively exposed (100) facets, which are highly favorable for the enhanced catalytic activity in nitro reduction. The reaction rate of nitro phenol to amino phenol over different Ag nanoshapes are 35.01 x 10⁻³ min⁻¹ (AgNCs/Al2O3), 8.28 x 10⁻³ min⁻¹ (AgNWs/Al2O3), 0.65 x 10⁻³ min⁻¹ (AgNSPs/Al2O3), respectively. The calculated thermodynamic parameters of the Ea values 23.6, 28.6 and 29.4 for the AgNC, AgNWs and AgNSP respectively.
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1,920 members
Mohane Selvaraj Coumar
  • Depatment of Bioinformatics
Subhankar Chatterjee
  • Department of Ecology and Environmental Sciences
Jambulingam Subramani
  • Department of Statistics
Raman Gurusamy
  • Department of Biotechnology
Hannah Rachel Vasanthi
  • Department of Biotechnology
RV Nagar, 605014, Puducherry, Pudhucherry, India
Head of institution
Dr.Gurmeet Singh