Detection and Genotyping of Coxiella-like Endosymbionts in Rhipicephalus and Haemaphysalis Ticks Infesting Pets and Livestock in Puducherry, India

Panneer Devaraju,Aravindhan Appakannu Gopal,Waseema Arif,Lakshmy Srinivasan,Terence Nathan Anthony,Mathivanan Ashokkumar 대한미생물학회 2024 Journal of Bacteriology and Virology Vol.54 No.1

Ticks are obligate blood-feeders that are vectors for several pathogens of public health and veterinary importance. Ticks were reported to have endosymbionts such as Coxiella-like, Francisella-like, Midichloria mitochondrii, Wolbachia, etc. With limited data on endosymbionts in ticks from India, we explored the endosymbiont diversity in ticks infesting the pets and livestock in Puducherry. Ectoparasites were collected from pet and domestic animals in 11 veterinary dispensaries between August to September 2022 and identified by taxonomical keys and sequencing of 16S rRNA, 18S rRNA, and Cytochrome oxidase subunit I genes. Wolbachia, Coxiella-like, Francisella-like and Midichloria mitochondrii endosymbionts were screened by PCR and their presence was confirmed by sequencing. A total of 984 ectoparasites including 5 tick, 3 lice, and 1 flea species were retrieved from 304 animals. Rhipicephalus sanguineus, Rhipicephalus haemaphysaloides, and Haemaphysalis bispinosa ticks were positive for the presence of Coxiella-like endosymbionts (CLEs) clustering under the clades B and C. Further, vertical transmission of CLEs in the field-collected R. sanguineus ticks was also demonstrated. This study offers an overview of the endosymbionts harbored by ticks in Puducherry with the first report of CLEs in H. bispinosa ticks and the transovarial transmission of endosymbionts in R. sanguineus ticks.

Large eddy simulation of the tornado-structure interaction to determine structural loadings

Panneer Selvam, R.,Millett, Paul C. Techno-Press 2005 Wind and Structures, An International Journal (WAS Vol.8 No.1

A tornado changes its wind speed and direction rapidly; therefore, it is difficult to study the effects of a tornado on buildings in a wind tunnel. The status of the tornado-structure interaction and various models of the tornado wind field found in literature are surveyed. Three dimensional computer modeling work using the turbulence model based on large eddy simulation is presented. The effect of a tornado on a cubic building is considered for this study. The Navier-Stokes (NS) equations are approximated by finite difference method, and solved by an semi-implicit procedure. The force coefficients are plotted in time to study the effect of the Rankine combined vortex model. The tornado is made to translate at a $0^{\circ}$ and $45^{\circ}$ angle, and the grid resolution is refined. Some flow visualizations are also reported to understand the flow behavior around the cube.

Synthesis, Characterization, and Antihyperglycemic Activity of Novel Oxazolidine Derivatives

Theivendren Panneer Selvam,Palanirajan Vijayaraj Kumar,Parthasarathi Ramu,Arumugam Siva Kumar 대한약학회 2011 Archives of Pharmacal Research Vol.34 No.6

A number of compounds have been prepared in order to improve pharmacological roles of antihyperglycemic activity. In the present paper, a series of 3-benzyl-2-(4'-substituted phenyl)-4(5H)-(4''-nitrophenyl amino)-1,3-oxazolidines (6a-e) were tested against hyperglycemia. Their antihyperglycemic activity was evaluated by streptozotocin (STZ) and sucrose-loaded (SLM) models. Compounds 6a, b, c, d, and e displayed significant reductions in blood glucose in the streptozotocin and sucrose loaded rat models. The purity of the synthesized compounds was characterized by means of IR, 1H-NMR, mass spectral and elemental analysis.

Synthesis of Novel 6,7,8,9-Tetrahydro-5H-5-hydroxyphenyl-2-benzylidine- 3-substituted Hydrazino Thiazolo (2,3-b) Quinazoline as Potent Antinociceptive and Anti-inflammatory Agents

T. Panneer Selvam,P. Vijayaraj Kumar 대한화학회 2010 Bulletin of the Korean Chemical Society Vol.31 No.11

A series of 6,7,8,9-tetrahydro-5H-5-hydroxyphenyl-2-benzylidine-3-substituted hydrazino thiazolo (2,3-b) quinazolines have been synthesized to meet the structural requirements essential for anti-inflammatory and antinociceptive properties. The synthesized series of heterocycles, 6,7,8,9-tetrahydro-5H-5-hydroxyphenyl-2-benzylidine-3-substituted hydrazino thiazolo (2,3-b) quinazoline by the reaction of 6,7,8,9-tetrahydro-5H-5-hydroxy phenyl thiazolo (2,3-b) quinazolin-3(2H)-one with appropriate hydrazine hydrate and ketones/aldehydes in the presence of anhydrous sodium acetate and glacial acetic acid as presented in Scheme 1. Their antinociceptive activity were evaluated by tailflick technique, anti-inflammatory was evaluated by carrageenan-induced paw edema test and their ulcerogenicity index determined by reported protocol. The compounds exhibited the lowest ulcer index (0.51 ± 1.63, 0.48 ± 1.28and 0.50 ± 1.53, respectively. The 6,7,8,9-tetrahydro-5H-5-hydroxy phenylhydroxy-2-benzylidine-3-(N'-3-pentylidenehydrazino)thiazolo (2,3-b) quinazoline and 6,7,8,9-tetrahydro-5H-5-hydroxy phenyl-2-benzylidine-3-(N'-2-pentylidene-hydrazino) thiazolo (2,3-b) quinazoline exhibited the most potent antinociceptive and anti-inflammatory activities.

Prediction of Surface Roughness using Spectral Analysis and Image Comparison of Audio Signals

R. Panneer,S. P. Harisubramanyabalaji,C. A. Sribalaji,A. Vivek,G. Vigneshwaran 한국정밀공학회 2016 International Journal of Precision Engineering and Vol.17 No.6

The aim of this work is to design an off-line system, method and experimental set-up for predicting surface roughness (Ra) of metal surfaces with the help of audio signals. The frictional contact between a metal surface and sharp pencil like scratching tool will produce audio signals which vary based on the roughness of the surface. The samples considered to design and validate the concept are work pieces machined with metal cutting processes such as Turning and Grinding. Several audio signals are generated from various types of metal surfaces produced by these processes after the completion of the machining process away from the machining area in an enclosed chamber. The audio waves are captured with the help of a microphone fixed inside the chamber. These audio signals are processed to generate the surface pattern of the relevant surface. The audio signals are then converted to spectrogram and normalized histogram plots with the help of MATLAB, based on which the roughness of the surfaces is predicted. An experimental set-up is designed which provides a sound-proof environment to capture and record the audio signals. The proposed system, method and set-up are validated with the actual surface roughness of the chosen surfaces measured with the help of a surface roughness measurement instrument.

Machine Learning Perspective Gene Optimization for Efficient Induction Machine Design

Ponmurugan Panneer Selvam,Rengarajan Narayanan 대한전기학회 2018 Journal of Electrical Engineering & Technology Vol.13 No.3

In this paper, induction machine operation efficiency and torque is improved using Machine Learning based Gene Optimization (ML-GO) Technique is introduced. Optimized Genetic Algorithm (OGA) is used to select the optimal induction machine data. In OGA, selection, crossover and mutation process is carried out to find the optimal electrical machine data for induction machine design. Initially, many number of induction machine data are given as input for OGA. Then, fitness value is calculated for all induction machine data to find whether the criterion is satisfied or not through fitness function (i.e., objective function such as starting to full load torque ratio, rotor current, power factor and maximum flux density of stator and rotor teeth). When the criterion is not satisfied, annealed selection approach in OGA is used to move the selection criteria from exploration to exploitation to attain the optimal solution (i.e., efficient machine data). After the selection process, two point crossovers is carried out to select two crossover points within a chromosomes (i.e., design variables) and then swaps two parent’s chromosomes for producing two new offspring. Finally, Adaptive Levy Mutation is used in OGA to select any value in random manner and gets mutated to obtain the optimal value. This process gets iterated till finding the optimal value for induction machine design. Experimental evaluation of ML-GO technique is carried out with performance metrics such as torque, rotor current, induction machine operation efficiency and rotor power factor compared to the state-of-the-art works.

Adaptive p-finite element for wind enigneering

R. Panneer Selvam,Zu-Qing Qu 한국풍공학회 2002 Wind and Structures, An International Journal (WAS Vol.5 No.2

Machine Learning Perspective Gene Optimization for Efficient Induction Machine Design

Selvam, Ponmurugan Panneer,Narayanan, Rengarajan The Korean Institute of Electrical Engineers 2018 Journal of Electrical Engineering & Technology Vol.13 No.3

In this paper, induction machine operation efficiency and torque is improved using Machine Learning based Gene Optimization (ML-GO) Technique is introduced. Optimized Genetic Algorithm (OGA) is used to select the optimal induction machine data. In OGA, selection, crossover and mutation process is carried out to find the optimal electrical machine data for induction machine design. Initially, many number of induction machine data are given as input for OGA. Then, fitness value is calculated for all induction machine data to find whether the criterion is satisfied or not through fitness function (i.e., objective function such as starting to full load torque ratio, rotor current, power factor and maximum flux density of stator and rotor teeth). When the criterion is not satisfied, annealed selection approach in OGA is used to move the selection criteria from exploration to exploitation to attain the optimal solution (i.e., efficient machine data). After the selection process, two point crossovers is carried out to select two crossover points within a chromosomes (i.e., design variables) and then swaps two parent's chromosomes for producing two new offspring. Finally, Adaptive Levy Mutation is used in OGA to select any value in random manner and gets mutated to obtain the optimal value. This process gets iterated till finding the optimal value for induction machine design. Experimental evaluation of ML-GO technique is carried out with performance metrics such as torque, rotor current, induction machine operation efficiency and rotor power factor compared to the state-of-the-art works.

Adaptive p-finite element method for wind engineering

Selvam, R. Panneer,Qu, Zu-Qing Techno-Press 2002 Wind and Structures, An International Journal (WAS Vol.5 No.2

An important goal of computational wind engineering is to impact the design process with simulations of flow around buildings and bridges. One challenging aspect of this goal is to solve the Navier-Stokes (NS) equations accurately. For the unsteady computations, an adaptive finite element technique may reduce the computer time and storage. The preliminary application of a p-version as well as an h-version adaptive technique to computational wind engineering has been reported in previous paper. The details on the implementation of p-adaptive technique will be discussed in this paper. In this technique, two posteriori error estimations, which are based on the velocity and vorticity, are first presented. Then, the polynomial order of the interpolation function is increased continuously element by element until the estimated error is less than the accepted. The second through sixth orders of hierarchical functions are used as the interpolation polynomials. Unequal order interpolations are used for velocity and pressure. Using the flow around a circular cylinder with Reynolds number of 1000 the two error estimators are compared. The result show that the estimated error based on the velocity is lower than that based on the vorticity.

Aeroelastic analysis of bridges using FEM and moving grids

Selvam, R. Panneer,Govindaswamy, S.,Bosch, Harold Techno-Press 2002 Wind and Structures, An International Journal (WAS Vol.5 No.2

In the recent years flow around bridges are investigated using computer modeling. Selvam (1998), Selvam and Bosch (1999), Frandsen and McRobie (1999) used finite element procedures. Larsen and Walther (1997) used discrete vorticity procedure. The aeroelastic instability is a major criterion to be checked for long span bridges. If the wind speed experienced by a bridge is greater than the critical wind speed for flutter, then the bridge fails due to aeroelastic instability. Larsen and Walther (1997) computed the critical velocity for flutter using discrete vortex method similar to wind tunnel procedures. In this work, the critical velocity for flutter will be calculated directly (free oscillation procedure) similar to the approaches reported by Selvam et al. (1998). It is expected that the computational time required to compute the critical velocity using this approach may be much shorter than the traditional approach. The computed critical flutter velocity of 69 m/s is in reasonable comparison with wind tunnel measurement. The no flutter and flutter conditions are illustrated using the bridge response in time.