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Lipases are the class of hydrolases with wide industrial applications. The present study analyses the stability of porcine pancreatic lipase (PPL) against urea, guanidine hydrochloride (Gdn), sodium dodecyl sulphate (SDS), and temperature using different spectroscopic techniques. Interestingly, this two-domain protein shows a two-state unfolding transition against urea and Gdn. The free energy of unfolding of PPL calculated from global analysis of the unfolding transitions obtained from different spectroscopic techniques is ~2.2 kcal/mol. In the presence of SDS, PPL shows a cooperative loss of secondary and tertiary structures above 0.2 mM of SDS. At above 2 mM of SDS, PPL forms irreversible, non-native, thermally stable structure. PPL loses its activity even at lower concentrations of urea (3 M), Gdn (0.5 M), and SDS (0.8 mM). Thermal denaturation of PPL shows an irreversible unfolding, and the protein lost its activity even by increasing the temperature to 45 °C. Though PPL in higher concentrations of SDS (>5 mM) shows stable conformation against temperature, its activity is completely lost. The results suggest that the structure and activity of PPL are more sensitive against chemical denaturants and temperature, and forms irreversible, non-native (in SDS) or completely unfolded (in urea, Gdn, and at higher temperature) conformations in different denaturing conditions.

The conventional detection process of direct sequence code division multiple access (DS-CDMA) is limited by multiple access interference (MAI) due to loss of orthogonality between spreading waveforms in multipath propagation channel environment.. In this paper RADICAL Independent Component Analysis (ICA) algorithm is proposed for detection of DS-CDMA signals and compared with FastICA, JADE ICA algorithm. Independent component analysis (ICA) is statistical technique based on higher order statistics, represent set random variables as linear transformation of statistically independent components and these conditions are satisfied in multi-user CDMA environment. Conventional methods mitigate sources of interference by taking into account all available information and at times seeking additional information channel characteristics, direction of arrival, etc. Combining an ICA element to conventional signal detection reduces multiple access interference (MAI) and enables a robust, computationally efficient structure. The proposed algorithm takes advantage of differential entropy estimation and converges quickly. Bit error rate simulations of these algorithms have been given and compared for different number of users, SNR. The simulation results show that RADICAL ICA algorithm performs best on detecting the source signals from the mixed CDMA signals.

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