Modeling the Dynamics of Implied Volatility Surface of S&P CNX NIFTY

This study is intended to apply and extend the accepted implied volatility modelling principles to the S&P CNX NIFTY (Index from National Stock Exchange of India - NSE) index options and account for the deviations in the volatility surface and the corresponding risk factors. The methodology followed for modelling implied volatility is similar to Dumas, Fleming and Whaley (DFW 1998) and Ishan Ullah Badshah (IUB – working paper 2008) and the methodology used for Principal Component Analysis is similar to the one applied by Skiadopolous, Hodges and Clewlow (SHC 1999). We compare the implied volatility surface generated using one linear model (constant volatility) and three nonlinear models that take into consideration varying levels of skew or smile and maturities. We find that the fourth model best captures all the characteristics of implied volatility. Secondly, we apply Principal Component Analysis (PCA) to the implied volatility surface and extract the most relevant principal components that explain most of the dynamics of the volatility surface. We determined that 80.66% to 94.47% of the variation in the IV surface is explained by the first three principal components. Lastly, we study the behaviour of the implied volatility surface of the S&P CNX NIFTY for two distinct periods – pre crisis (2006) and post crisis (2009). Specific applications of the model include pricing and hedging of derivatives and risk management

Bioefficacy and dissipation of ?-cyfluthrin against white fly Bemisia tabaci Genn.) in okra (Abelomoschus esculentus L.)

A field experiment was conducted to evaluate the efficacy of different insecticides viz., bifenthrin, flubendiamide, fipronil, quinalphos, pronofos and ?-cyfluthrin against white fly (Bemisia tabaci) of okra (Abelomoschus esculentus) by spraying twice. Among the insecticides evaluated, ? cyfluthrin at 18.75 g a.iha-1 was found to be the effective by registering 57.00 and 54.21 per cent reduction of whitefly (B. abaci) during first and second sprays, respectively. Further ?-cyfluthrin at 18.75 g a. i ha-1 was subjected to dissipation studies by collecting okra (A. esculentus) fruit samples at interval of zero, one, three, five, seven, 10 and 15 days after last spray. Results of the dissipation studies showed that the initial deposits of ?-cyfluthrin (18.75 g a.iha-1) in okra (A. esculentus) fruit sample was registered to be 0.11 mg kg-1 and dissipated to below detectable level (BDL) within five days after spray

A comparison of the proprioception of osteoarthritic knees and post total knee arthroplasty

Background: Proprioception of the knee joint is an important factor for establishing balance, and smooth walking. The effect of arthroplasty on proprioception can be a determinant of post-operative function and subjective feeling of the arthroplasty. We wished to check the status of osteoarthritic knees and how their proprioceptive function is, in comparison to knees post total knee replacement.Methods: We compared 80 unilateral knee replacement patients with their osteoarthritic counterpart in the opposite knee. There was 50% Cruciate Retaining (n =40), Posterior Stabilized 50% (n =40). We assessed the proprioception using threshold to detection of passive motion and conscious awareness of passive joint position.Results: 73.8% (n =59) of patients experienced a better joint position sense, 21% (n =17) had decreased joint position sense and 5% (n =4) had the same, when compared to the contralateral osteoarthritic knee. The mean of threshold to detection of passive motion was 2.16+0.68 for the replaced knees versus 2.72±0.61 for the contralateral osteoarthritic knee.Conclusions: The proprioception of the knees that were replaced with arthroplasties had a better proprioceptive function then the osteoarthritic knees. This further solidifies the reasons to replace the dysfunctional osteoarthritic knee.

Using RRC Algorithm Classify the Proteins and Visualize in Biological Databases

Visualize biological database for protein is very complicated without Classify the protein properties.Protein classification is one of the major application of machine learning algorithms in the field of bio-informatics.The searching classification model works in two steps.Firstly, the correlation based feature selection for protein classification will be taken and strongly correlated features will be considered for classification using MST based . In second step, using Robust Regression, the classification will be performed. Based on results of RRC algorithm, it is highly has classification ratio than traditional machine learning algorithms such as SVM, Na�ve-bayes , Decision Trees

Using RRC Algorithm Classify the Proteins and Visualize in Biological Databases

Visualize biological database for protein is very complicated without Classify the protein properties.Protein classification is one of the major application of machine learning algorithms in the field of bio-informatics.The searching classification model works in two steps.Firstly, the correlation based feature selection for protein classification will be taken and strongly correlated features will be considered for classification using MST based . In second step, using Robust Regression, the classification will be performed. Based on results of RRC algorithm, it is highly has classification ratio than traditional machine learning algorithms such as SVM, Na�ve-bayes , Decision Trees

Indigenous Development of a Track Etch Detector

Solid state nuclear track detectors (SSNTDs) have been recognised by IAEA as a standard method for estimation of radon, thoron and their daughter products in the environment. The detectors that are commonly used in environmental monitoring are generally made from cellulose nitrate (LR-115) and polycarbonates (CR-39). In view of the non-availability of these detectors in India, need was felt to develop them indigenously. Accordingly, an attempt has been made to develop cellulose nitrate films for their use in SSNTD. Cellulose nitrate with a particular nitrogen content was used for preparing these films by a cast method. This films were annealed, evaluated and then compared with imported films. The background track density and alpha track density after exposure to 150 nCi of /sup 241/Am source at 2.5 cm distance were found to be comparable with those of imported films

Association of facet orientation and tropism with lumbar disc herniation

Background: Intervertebral disc herniation is a degenerative lumbar disease and a common pathology of skeletal system. Currently, most experts assume that facet tropism may affect lumbar degenerative diseases. Considering the previous inconsistent findings on the relationship of facet tropism, the present study was aimed to find the association between facet tropism and lumbar disc herniation.Methods: Patients with low back pain attending the OPD of orthopaedics department, with signs and symptoms of disc herniation were sent for magnetic resonance imaging (MRI). 72 patients with single level disc herniation were included in the study. Facet angles were measured using MRI of 1.5 T using the method described by Karacan et al. Facet tropism was defined as difference of 100 or more in facet joint angles between right and left sides.Results: 45 of the 72 cases (50%) who presented with lumbar disc herniation (LDH) had tropism while none (0%) at the control level did. This association was not statistically significant (p=0.983). Significant association was found between the side of disc herniation and the distribution of the more coronal or sagittal facing facet (p=0.024).Conclusions: Despite the presence of tropism only in the intervertebral segments affected with LDH in our study, the association between tropism and LDH was not statistically significant