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Eeda Venkateswara Rao,Vinay Kumar Sharma,Niti Sharma,Young-Soo Kim,Sang-Hun Jung 충남대학교 약학대학 의약품개발연구소 2014 藥學論文集 Vol.29 No.-
To define the role of substituents of chalcones as potent MD-2 inhibitors, we designed and synthesized analogs of 1-(2-hydroxy-6-(isopentyloxy)phenyl)-3-(4-hydroxyphenyl)prop-2-en-1-one (1) for their in vitro activities against RAW 264.7 cell using the SEAP assay as well as for LPS displacement assay. Among all the derivatives, compound 5 (IC50=27.3 μM), showed good inhibition of NF-κB activation by blocking the TLR4-mediated NF-κB activation signalling in RAW 264.7 as well as the rhMD-2 binding to immobilized LPS with 53% inhibition at 30 μM. The SAR studies indicated that small alkyl group like 3-methylbutoxy at 6-position of ring A and substituent with hydrogen bonding capability at 4-position of ring B of chalcone should be very important for inhibition of LPS induced NF-κB activation and LPS displacement of MD-2.
Enhance Health Risks Prediction Mechanism in the Cloud Using RT-TKRIBC Technique
Konduru, Venkateswara Raju,Bharamgoudra, Manjula R The Korea Institute of Information and Commucation 2021 Journal of information and communication convergen Vol.19 No.3
A large volume of patient data is generated from various devices used in healthcare applications. With increase in the volume of data generated in the healthcare industry, more wellness monitoring is required. A cloud-enabled analysis of healthcare data that predicts patient risk factors is required. Machine learning techniques have been developed to address these medical care problems. A novel technique called the radix-trie-based Tanimoto kernel regressive infomax boost classification (RT-TKRIBC) technique is introduced to analyze the heterogeneous health data in the cloud to predict the health risks and send alerts. The infomax boost ensemble technique improves the prediction accuracy by finding the maximum mutual information, thereby minimizing the mean square error. The performance evaluation of the proposed RT-TKRIBC technique is realized through extensive simulations in the cloud environment, which provides better prediction accuracy and less prediction time than those provided by the state-of-the-art methods.
Solvothermal synthesis and characterization of silver nanoparticles
Guptha, K. Venkateswara,Nesaraj, A. Samson Techno-Press 2014 Advances in nano research Vol.2 No.3
Among the various nanoparticles reported for commercial applications, considerable interest has been generated by the use of silver nanoparticles. Owning to extremely small size, silver nanoparticles exhibit enhanced properties when compared with the bulk material. In this research work, silver nanoparticles were prepared by the reduction of silver salt with a reducing agent by a solvothermal method using different solvent mediums such as ethanol, hexane, toluene and acetone with water. The prepared silver nanoparticles were characterized systematically by X-ray diffraction (XRD), particle size analysis and scanning electron microscope (SEM). The results revealed the formation of pure silver phase and nano-sized particles. Among the different solvent mediums used, the silver nanoparticles prepared by hexane and water as solvent mixture resulted in very low particle size.
Dayakar, T.,Venkateswara Rao, K.,Park, Jinsub,Sadasivuni, Kishor Kumar,Ramachandra Rao, K.,Jaya rambabu, N. Elsevier 2018 Materials chemistry and physics Vol.216 No.-
<P><B>Abstract</B></P> <P>An enzyme-free glucose sensor developed based on silver nanoparticles (Ag NPs) via bio-mediated route using <I>Ocimum tenuiflorum</I> leaves extract. The Ag NPs were characterized by X-ray diffraction (XRD), ultraviolet-visible (UV-Vis) spectroscopy, Fourier transform infrared (FTIR) spectroscopy, Particle size analyzer (PSA), Scanning electron microscopy (SEM), Energy-dispersive X-ray (EDAX) spectroscopy, and Transmission electron microscopy (TEM), to study structural, optical and morphological properties. The electrocatalytic activity of Ag NPs towards the oxidation of glucose in the 0.1 M NaOH electrolyte solution was analyzed. The Ag NPs was coated on Glassy carbon electrode (GCE) and reports indicating the outstanding capability such as high sensitivity (895.8 μAmM<SUP>−1</SUP>cm<SUP>−2</SUP>), linear range (1–8.9 mM), response time (<4s), low detection limit (0.0048 μM, S/N = 3), long-term stability, reproducibility, repeatability, and selectivity of the sensor. Therefore, the bio-synthesized Ag NPs can markedly helpful to fabricate non-enzymatic, sustainable, simple, low cost, and eco-friendly glucose monitoring devices.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Ocimum tenuiflorum leaf extract and silver nitrate were used to prepare Ag NPs. </LI> <LI> Structural, optical and morphological properties of Ag NPs were studied. </LI> <LI> The GCE modified with Ag NPs showed a sensitivity of 895.8 μAmM<SUP>−1</SUP>cm<SUP>−2</SUP>. </LI> <LI> Bio-mediated synthesized NPs showed sustainable glucose sensing properties. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>
Singh, Gajbir,Rao, G. Venkateswara,Iyengar, N.G.R. Techno-Press 1995 Structural Engineering and Mechanics, An Int'l Jou Vol.3 No.2
It is well known that two-dimensional simplified third-order theories satisfy the layer interface continuity of transverse shear strains, thus these theories violate the continuity of transverse shear stresses when two consecutive layers differ either in fibre orientation or material. The third-order theories considered herein involve four/or five dependent unknowns in the displacement field and satisfy the condition of vanishing of transverse shear stresses at the bounding planes of the plate. The objective of this investigation is to examine (i) the flexural response prediction accuracy of these third-order theories compared to exact elasticity solution (ii) the effect of layer interface continuity conditions on the flexural response. To investigate the effect of layer interface continuity conditions, three-dimensional elasticity solutions are developed by enforcing the continuity of different combinations of transverse stresses and/or strains at the layer interfaces. Three dimensional twenty node solid finite element (having three translational displacements as degrees of freedom) without the imposition of any of the conditions on the transverse stresses and strains is also employed for the flexural analysis of the laminated plates for the purposes of comparison with the above theories. These shear deformation theories and elasticity approaches in terms of accuracy, adequacy and applicability are examined through extensive numerical examples.
V.Sucharita,P.Venkateswara Rao,Debnath Bhattacharyya,Tai-hoon Kim 보안공학연구지원센터 2016 International Journal of Bio-Science and Bio-Techn Vol.8 No.1
This research is to present a new approach for the classification of the Penaeid Prawn Species. The extraction of Texture features based on the Gabor filter is proposed in this method. These extracted features are used for the classification of Penaeid Prawn Species based on Radial Basis Probabilistic Neural Networks and Support Vector Machines. The texture of the prawn image are extracted based on different scales and orientations by which mean and standard deviation are calculated. The resultant Gabor feature values are fed as input to Radial basis Probabilistic Neural Network Classifier for the classification of the species. The experimental results show the performance of the extracted feature vectors for Penaeid Prawn species recognition. The RBPNN gives better recognition when compared with Support vector machines.
Sadra Souzanchi,Laleh Nazari,Kasanneni Tirumala Venkateswara Rao,Zhongshun Yuan,Zhongchao Tan,Chunbao Charles Xu 한국공업화학회 2021 Journal of Industrial and Engineering Chemistry Vol.101 No.-
This work aimed to produce 5-hydroxymethylfurfural (5-HMF) from glucose in a biphasic continuousflowtubular reactor with various heterogeneous solid acid catalysts or combined solid acid-base catalysts. Among the catalysts tested, niobium phosphate (NbP) was found to be the most active catalystfor glucose dehydration with a maximum 5-HMF yield of 45% at 150 C. The higher activity of NbPwas attributed to its higher total number of acid sites and BET surface area, as well as the presence of bothLewis acid and Brønsted acid sites. The effects of different operating conditions such as aqueous toorganic (A/O) phase ratio, reaction temperature and feeding flow rate on the activity of some selected catalystswere studied. Reducing A/O ratio by increasing the extracting organic phase flow rate and increasingthe reaction temperature (up to 150 C) were found to positively affect 5-HMF production fromglucose in the presence of NbP. Kinetics study demonstrated that the overall reaction of glucose dehydrationto 5-HMF over the NbP catalyst is a first-order reaction with the reaction rate constants (k) determinedas 0.06, 0.21 and 0.6 min 1 at 110, 130 and 150 C, respectively, and the apparent activationenergy (Ea) calculated to be 77 kJ/mol.
Conditional Density based Statistical Prediction
J Rama Devi,K. Koteswara Rao,M Venkateswara Rao International Journal of Computer ScienceNetwork S 2023 International journal of computer science and netw Vol.23 No.6
Numerous genuine issues, for example, financial exchange expectation, climate determining and so forth has inalienable arbitrariness related with them. Receiving a probabilistic system for forecast can oblige this dubious connection among past and future. Commonly the interest is in the contingent likelihood thickness of the arbitrary variable included. One methodology for expectation is with time arrangement and auto relapse models. In this work, liner expectation technique and approach for computation of forecast coefficient are given and likelihood of blunder for various assessors is determined. The current methods all need in some regard assessing a boundary of some accepted arrangement. In this way, an elective methodology is proposed. The elective methodology is to gauge the restrictive thickness of the irregular variable included. The methodology proposed in this theory includes assessing the (discretized) restrictive thickness utilizing a Markovian definition when two arbitrary factors are genuinely needy, knowing the estimation of one of them allows us to improve gauge of the estimation of the other one. The restrictive thickness is assessed as the proportion of the two dimensional joint thickness to the one-dimensional thickness of irregular variable at whatever point the later is positive. Markov models are utilized in the issues of settling on an arrangement of choices and issue that have an innate transience that comprises of an interaction that unfurls on schedule on schedule. In the nonstop time Markov chain models the time stretches between two successive changes may likewise be a ceaseless irregular variable. The Markovian methodology is especially basic and quick for practically all classes of classes of issues requiring the assessment of contingent densities.