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Search Results: 1 - 10 of 130763 matches for " V. Naresh "
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Structural and Optical Properties of Li+: PVP & Ag+: PVP Polymer Films  [PDF]
Kothapalle Sivaiah, Koramala Naveen Kumar, V. Naresh, Srinivasa Buddhudu
Materials Sciences and Applications (MSA) , 2011, DOI: 10.4236/msa.2011.211225
Abstract: PVP polymers containing Li+ or Ag+ Ions have been synthesized in good stability and transparency by using the solution casting method. Their structural, optical, thermal and electrical properties have been investigated from the measurement of XRD, FTIR, SEM, EDAX, optical absorption spectra, TG-DTA profiles and impedance spectral features in order to evaluate their potentialities for their use in electrochemical display device applications.
Nimotuzumab with Concurrent Chemo-Radiotherapy in Patients with Locally Advanced Squamous Cell Carcinoma of Head and Neck (LASCCHN)  [PDF]
Naresh Somani
Journal of Cancer Therapy (JCT) , 2015, DOI: 10.4236/jct.2015.64038
Abstract:

Background: Head and neck cancers (HNCs) constitute 5% of all cancers globally and are the most common cancers in India. Chemotherapy and radiotherapy have not been proved to be effective in advanced cases and the prognosis remains dismal. This underscores the need for newer treatment options in these cases. Nimotuzumab, an anti-epidermal growth factor receptor (anti-EGFR) monoclonal antibody, was safer when combined with chemo- or radio-therapy. Aim: To evaluate the safety and efficacy of concurrently administered nimotuzumab with chemo-radiotherapy in patients with advanced inoperable squamous cell carcinomas of head and neck (LASCCHN). Methods:This was an open-label, single arm study evaluating 57 patients with histologically confirmed inoperable LASCCHN (stages III and IV) and eastern co-operative oncology group (ECOG) performance status < 2. Informed consent was obtained from all patients. The patients were administered IV cisplatin 30 mg/m2and IV nimotuzumab 200 mg weekly for 6 weeks, along with radiotherapy of 6600 cGy over 33 fractions. Patients were evaluated over response evaluation criteria in solid tumors (RECIST) criteria 24 weeks after the last cycle of chemotherapy. Results: Mean age of patient was 50 years old (29 - 79 years old). The most common site of cancer was oral cavity (56.1%). Forty six patients (80.7%) completed 6 cycles of therapy. Objective response rate (ORR) was 80.7%, with 34 patients (59.6%) achieving complete response (CR), and 12 (21%) achieving partial response (PR). Stable disease (SD) was noted in 8 (14%) patients and progressive disease in 3 (5.2%) patients. Conclusion: Addition of nimotuzumab is a safe and efficacious option in patients with inoperable LASCCHN. Our observations confirm the available Phase II data. The long term survival benefits based on this encouraging response rate need to be further evaluated in this subset of cancer patients.

A Stability Indicating U-HPLC Method for Milnacipran in Bulk Drugs and Pharmaceutical Dosage Forms  [PDF]
Naresh Tondepu, Shakil S. Sait, K.V. Surendranath, Ravi Kiran Kaja, Suresh Kumar
American Journal of Analytical Chemistry (AJAC) , 2012, DOI: 10.4236/ajac.2012.31007
Abstract: The objective of the current study was to develop a validated, specific and stability-indicating reverse phase UHPLC method for the quantitative determination of Milnacipran and its related substances. The determination was done for active pharmaceutical ingredient and its pharmaceutical dosage forms in the presence of degradation products, and its process-related impurities. The drug was subjected to stress conditions of hydrolysis (acid and base), oxidation, pho- tolysis and thermal degradation per International Conference on Harmonization (ICH) prescribed stress conditions to show the stability-indicating power of the method. Significant degradation was observed during acid, base, oxidative and neutral stress hydrolysis. The chromatographic conditions were optimized using an impurity-spiked solution and the samples generated from forced degradation studies. In the developed UHPLC method, the resolution between Milnacipran and its process-related impurities was found to be greater than 2.0. Regression analysis shows an r value (correlation coefficient) of greater than 0.999 for Milnacipran and it’s all the five impurities. The chromatographic separation was achieved on a C18 stationary phase. The method employed a linear gradient elution and the detection wavelength was set at 220 nm. The mobile phase consists of buffer and acetonitrile delivered at a flow rate of 0.2 mL?min–1. Buffer consists a mixture of 10 mM Sodium dihydrogen phosphate monohydrate and 10 mM hexane sulfonate sodium salt, pH adjusted to 2.5 using ortho phosphoric acid. The mobile phase A consists of buffer and acetonitrile (950:50, v/v) and mobile phase B consists of acetonitrile. The stress samples were assayed against a qualified reference standard and the mass balance was found to be close to 99.5%. The developed RP-LC method was validated with respect to linearity, accuracy, precision and robustness.
A Stability Indicating HPLC Method for Dronedarone in Bulk Drugs and Pharmaceutical Dosage Forms  [PDF]
Naresh Tondepu, Shakil S. Sait, K.V. Surendranath, Ravi Kiran Kaja, Suresh Kumar
American Journal of Analytical Chemistry (AJAC) , 2012, DOI: 10.4236/ajac.2012.38072
Abstract: The objective of the current study was to develop a validated, specific and stability-indicating reverse phase HPLC method for the quantitative determination of Dronedarone and its related substances. The determination was done for active pharmaceutical ingredient and its pharmaceutical dosage forms in the presence of degradation products, and its process-related impurities. The drug was subjected to stress conditions of hydrolysis (acid and base), oxidation, photolysis and thermal degradation per International Conference on Harmonization (ICH) prescribed stress conditions to show the stability-indicating power of the method. Significant degradation was observed during acid, oxidative and photo stress studies. In the developed HPLC method, the resolution between Dronedarone and its process-related impurities was found to be greater than 2.0. Regression analysis shows an r value (correlation coefficient) of greater than 0.999 for Dronedarone and it’s all the five impurities. The chromatographic separation was achieved on a C8 stationary phase. The method employed a linear gradient elution and the detection wavelength was set at 288 nm. The stress samples were assayed against a qualified reference standard and the mass balance was found to be close to 99.6%. The developed HPLC method was validated with respect to linearity, accuracy, precision and robustness.
Optimal Hydro-Thermal Generation Scheduling Using an Efficient Feedback Neural Network Optimization Model
V. Sharma,R. Naresh,Sushil,Deepika Yadav
Research Journal of Applied Sciences, Engineering and Technology , 2011,
Abstract: This study demonstrates the use of a high-performance feedback neural network optimizer based on a new idea of successive approximation for finding the hourly optimal release schedules of interconnected multi-reservoir power system in such a way to minimize the overall cost of thermal generations spanned over the planning period. The main advantages of the proposed neural network optimizer over the existing neural network optimization models are that no dual variables, penalty parameters or lagrange multipliers are required. This network uses a simple structure with the least number of state variables and has better asymptotic stability. For an arbitrarily chosen initial point, the trajectory of the network converges to an optimal solution of the convex nonlinear programming problem. The proposed optimizer has been tested on a nonlinear practical system consisting of a multi-chain cascade of four linked reservoir type hydro-plants and a number of thermal units represented by a single equivalent thermal power plant and so obtained results have been validated using conventional conjugate gradient method and genetic algorithm based approach.
Effective Biosorption of Nickel(II) from Aqueous Solutions Using Trichoderma viride
P. Sujatha,V. Kalarani,B. Naresh Kumar
Journal of Chemistry , 2013, DOI: 10.1155/2013/716098
Abstract:
Estimation of the parameters of an infectious disease model using neural networks
V. Sree Hari Rao,M. Naresh Kumar
Computer Science , 2015, DOI: 10.1016/j.nonrwa.2009.04.006
Abstract: In this paper, we propose a realistic mathematical model taking into account the mutual interference among the interacting populations. This model attempts to describe the control (vaccination) function as a function of the number of infective individuals, which is an improvement over the existing susceptible ?infective epidemic models. Regarding the growth of the epidemic as a nonlinear phenomenon we have developed a neural network architecture to estimate the vital parameters associated with this model. This architecture is based on a recently developed new class of neural networks known as co-operative and supportive neural networks. The application of this architecture to the present study involves preprocessing of the input data, and this renders an efficient estimation of the rate of spread of the epidemic. It is observed that the proposed new neural network outperforms a simple feed-forward neural network and polynomial regression.
Novel Approaches for Predicting Risk Factors of Atherosclerosis
V. Sree Hari Rao,M. Naresh Kumar
Computer Science , 2015, DOI: 10.1109/TITB.2012.2227271
Abstract: Coronary heart disease (CHD) caused by hardening of artery walls due to cholesterol known as atherosclerosis is responsible for large number of deaths world-wide. The disease progression is slow, asymptomatic and may lead to sudden cardiac arrest, stroke or myocardial infraction. Presently, imaging techniques are being employed to understand the molecular and metabolic activity of atherosclerotic plaques to estimate the risk. Though imaging methods are able to provide some information on plaque metabolism they lack the required resolution and sensitivity for detection. In this paper we consider the clinical observations and habits of individuals for predicting the risk factors of CHD. The identification of risk factors helps in stratifying patients for further intensive tests such as nuclear imaging or coronary angiography. We present a novel approach for predicting the risk factors of atherosclerosis with an in-built imputation algorithm and particle swarm optimization (PSO). We compare the performance of our methodology with other machine learning techniques on STULONG dataset which is based on longitudinal study of middle aged individuals lasting for twenty years. Our methodology powered by PSO search has identified physical inactivity as one of the risk factor for the onset of atherosclerosis in addition to other already known factors. The decision rules extracted by our methodology are able to predict the risk factors with an accuracy of $99.73%$ which is higher than the accuracies obtained by application of the state-of-the-art machine learning techniques presently being employed in the identification of atherosclerosis risk studies.
A New Methodology for Estimating Internal Credit Risk and Bankruptcy Prediction under Basel II Regime
M. Naresh Kumar,V. Sree Hari Rao
Quantitative Finance , 2015, DOI: 10.1007/s10614-014-9452-9
Abstract: Credit estimation and bankruptcy prediction methods have been utilizing Altman's $z$ score method for the last several years. It is reported in many studies that $z$ score is sensitive to changes in accounting figures. Researches have proposed different variations to conventional $z$ score that can improve the prediction accuracy. In this paper we develop a new multivariate non-linear model for computing the $z$ score. In addition we develop a new credit risk index by fitting a Pearson type-III distribution to the transformed financial ratios. The results from our study have shown that the new $z$ score can predict the bankruptcy with an accuracy of $98.6\%$ as compared to $93.5\%$ by the Altman's $z$ score. Also, the discriminate analysis revealed that the new transformed financial ratios could predict the bankruptcy probability with an accuracy of $93.0\%$ as compared to $87.4\%$ using the weights of Altman's $z$ score.
Fractures in patients of chronic kidney disease on maintenance hemodialysis
Sivakumar V,Naveen P,Naresh V.V.,Sivaramakrishna D
Saudi Journal of Kidney Diseases and Transplantation , 2011,
Abstract:
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