Novel [3+2] annulation reaction of nitrones with Burgess reagent and a few related reactions

Burgess reagent first prepared by E. M. Burgess in 1968, is a mild and selective dehydrating agent for secondary and tertiary alcohols and due to the amphipolar nature it is gainfully employed in a number of creative synthetic ventures. A close examination of the structure of Burgess reagent reveals that it can act as a 1,2-dipole. To the best of our knowledge, no attempts have been made to tap full synthetic potential of the amphipolar nature of this reagent and no reports on 1,3-dipolar addition to a σ-bond in acyclic systems are available in literature. In this context, we propose to unravel novel applications of Burgess reagent based on its amphipolar nature. Rich and multifaceted chemistry of nitrones form the basis of many successful chemical transformations used in attractive synthetic strategies. For the last 50 years special attention has been given to nitrones due to their successful application as building blocks in the synthesis of various natural and biologically active compounds. Our interest in nitrones stems out of its unique character: i.e. it is a 1,3-dipole exhibiting distinct nucleophilic activity. We reasoned that 1,3-dipole possessing significant nucleophilicity should react with amphipolar Burgess reagent with elimination of triethylamine to give the corresponding five-membered ring product by formal dipolar addition to a σ bond. To test this hypothesis we studied the reaction of nitrones with Burgess reagent. This thesis reveals our attempts to explore the [3+2] annulation reaction of nitrones with Burgess reagent which was found to be followed by a rearrangementinvolving C-to-N aryl migration, ultimately resulting in diarylamines and carbamates. We have also examined the reaction of cyanuric chloride with nitrones in DMF with a view to exploit the nucleophilicty of nitrones and to unravel the migratory aptitude, if any, observed in this reaction

Characterization of Linear Low-Density Polyethylene/ Poly(vinyl alcohol) Blends and Their Biodegradability by Vibrio sp. Isolated from Marine Benthic Environment

Increasing amounts of plastic waste in the environment have become a problem of gigantic proportions. The case of linear low-density polyethylene (LLDPE) is especially significant as it is widely used for packaging and other applications. This synthetic polymer is normally not biodegradable until it is degraded into low molecular mass fragments that can be assimilated by microorganisms. Blends of nonbiodegradable polymers and biodegradable commercial polymers such as poly (vinyl alcohol) (PVA) can facilitate a reduction in the volume of plastic waste when they undergo partial degradation. Further, the remaining fragments stand a greater chance of undergoing biodegradation in a much shorter span of time. In this investigation, LLDPE was blended with different proportions of PVA (5–30%) in a torque rheometer. Mechanical, thermal, and biodegradation studies were carried out on the blends. The biodegradability of LLDPE/PVA blends has been studied in two environments: (1) in a culture medium containing Vibrio sp. and (2) soil environment, both over a period of 15 weeks. Blends exposed to culture medium degraded more than that exposed to soil environment. Changes in various properties of LLDPE/PVA blends before and after degradation were monitored using Fourier transform infrared spectroscopy, a differential scanning calorimeter (DSC) for crystallinity, and scanning electron microscope (SEM) for surface morphology among other things. Percentage crystallinity decreased as the PVA content increased and biodegradation resulted in an increase of crystallinity in LLDPE/PVA blends. The results prove that partial biodegradation of the blends has occurred holding promise for an eventual biodegradable product

Product autoregressive models for non-negative variables

When variables in time series context are non-negative, such as for volatility, survival time or wave heights, a multiplicative autoregressive model of the type Xt = Xα t−1Vt , 0 ≤ α < 1, t = 1, 2, . . . may give the preferred dependent structure. In this paper, we study the properties of such models and propose methods for parameter estimation. Explicit solutions of the model are obtained in the case of gamma marginal distribution

Analysis of Stochastic Volatility Sequences Generated by Product Autoregressive Models

The classical methods of analysing time series by Box-Jenkins approach assume that the observed series uctuates around changing levels with constant variance. That is, the time series is assumed to be of homoscedastic nature. However, the nancial time series exhibits the presence of heteroscedasticity in the sense that, it possesses non-constant conditional variance given the past observations. So, the analysis of nancial time series, requires the modelling of such variances, which may depend on some time dependent factors or its own past values. This lead to introduction of several classes of models to study the behaviour of nancial time series. See Taylor (1986), Tsay (2005), Rachev et al. (2007). The class of models, used to describe the evolution of conditional variances is referred to as stochastic volatility modelsThe stochastic models available to analyse the conditional variances, are based on either normal or log-normal distributions. One of the objectives of the present study is to explore the possibility of employing some non-Gaussian distributions to model the volatility sequences and then study the behaviour of the resulting return series. This lead us to work on the related problem of statistical inference, which is the main contribution of the thesis