Cochin University of Science and Technology

About: Cochin University of Science and Technology is a education organization based out in Kochi, Kerala, India. It is known for research contribution in the topics: Thin film & Natural rubber. The organization has 5382 authors who have published 7690 publications receiving 103827 citations. The organization is also known as: CUSAT & Cochin University.

Blends of bisphenol A‐based cyanate ester and bismaleimide: Cure and thermal characteristics

Abstract: A dicyanate ester, namely, 2,2-bis-(4-cyanatophenyl)propane, and a bismaleimide, namely, 2,2-bis[4-(4-maleimido phenoxy)phenyl]propane, possessing closely resembling backbone structures, were cured together to derive bismaleimide–triazine network polymers of varying compositions. The blend manifested a eutectic melting behavior at a 1 : 1 composition with a eutectic melting point of 15°C. The cure characterization of the blends was done by DSC and dynamic mechanical analyses (DMA). The near simultaneous cure of the blend could be transformed to a clear sequential one by catalyzing the dicyanate cure to lower temperature using dibutyl tin dilaurate. The two-stage, independent cure of the components of the blend evidenced in DSC was confirmed by DMA. The cure profile of the bismaleimide component predicted from the kinetic data derived from nonisothermal DSC was found to be in league with the isothermal DMA behavior. Both techniques led to optimization of the cure schedule of the blends. The cured polymers were characterized by FTIR and TGA. The cured blends underwent decomposition in two stages, each corresponding to the polycyanurate and polybismaleimide. Enhancing the bismaleimide component did not alter the initial decomposition temperature, but led to reduced rate of thermal degradation at higher temperature. Interlinking of the two networks and enhancing crosslink density through coreaction of the blend with 4-cyantophenylmaleimide unaffected the initial decomposition properties but was conducive for increasing the char residue significantly. Computation of activation parameters for the thermal decomposition of the polymers confirmed that the first step in the degradation of the blends is caused by the polycyanurate component. © 1999 John Wiley & Sons, Inc. J Appl Polym Sci 74: 3365–3375, 1999

Link between convection and meridional gradient of sea surface temperature in the Bay of Bengal

Abstract: We use daily satellite estimates of sea surface temperature (SST) and rainfall during 1998–2005 to show that onset of convection over the central Bay of Bengal (88–92°E, 14–18°N) during the core summer monsoon (mid-May to September) is linked to the meridional gradient of SST in the bay. The SST gradient was computed between two boxes in the northern (88–92°E, 18–22°N) and southern (82–88°E, 4–8°N) bay; the latter is the area of the cold tongue in the bay linked to the Summer Monsoon Current. Convection over central bay followed the SST difference between the northern and southern bay (ΔT) exceeding 0.75°C in 28 cases. There was no instance of ΔT exceeding this threshold without a burst in convection. There were, however, five instances of convection occurring without this SST gradient. Long rainfall events (events lasting more than a week) were associated with an SST event (ΔT ≥ 0.75°C); rainfall events tended to be short when not associated with an SST event. The SST gradient was important for the onset of convection, but not for its persistence: convection often persisted for several days even after the SST gradient weakened. The lag between ΔT exceeding 0.75°C and the onset of convection was 0–18 days, but the lag histogram peaked at one week. In 75% of the 28 cases, convection occurred within a week of ΔT exceeding the threshold of 0.75°C. The northern bay SST, TN, contributed more to ΔT, but it was a weaker criterion for convection than the SST gradient. A sensitivity analysis showed that the corresponding threshold for TN was 29°C. We hypothesise that the excess heating (∼1°C above the threshold for deep convection) required in the northern bay to trigger convection is because this excess in SST is what is required to establish the critical SST gradient.

Failure of teicoplanin therapy in two neutropenic patients with staphylococcal septicemia who recovered after administration of vancomycin.

Abstract: A report is given on two neutropenic patients with staphylococcal septicemia caused byStaphylococcus haemolyticus andStaphylococcus aureus (both strains methicillin-resistant) who failed to respond to therapy with teicoplanin. Both strains were resistant to teicoplanin (MIC 16 and 8 mg/l respectively), but remained sensitive to vancomycin (MIC 2 and 4 mg/l respectively). Replacement of teicoplanin with vancomycin led to full recovery of both patients and their discharge from hospital. These two cases emphasize the importance of clinical and microbiological monitoring of patients with staphylococcal septicemia, even when glycopeptides are used for treatment.

Modeling chaotic behavior of stock indices using intelligent paradigms

Abstract: The use of intelligent systems for stock market predictions has been widely established. In this paper, we investigate how the seemingly chaotic behavior of stock markets could be well represented using several connectionist paradigms and soft computing techniques. To demonstrate the different techniques, we considered Nasdaq-100 index of Nasdaq Stock MarketSM and the S&P CNX NIFTY stock index. We analyzed 7 year's Nasdaq 100 main index values and 4 year's NIFTY index values. This paper investigates the development of a reliable and efficient technique to model the seemingly chaotic behavior of stock markets. We considered an artificial neural network trained using Levenberg-Marquardt algorithm, Support Vector Machine (SVM), Takagi-Sugeno neurofuzzy model and a Difference Boosting Neural Network (DBNN). This paper briefly explains how the different connectionist paradigms could be formulated using different learning methods and then investigates whether they can provide the required level of performance, which are sufficiently good and robust so as to provide a reliable forecast model for stock market indices. Experiment results reveal that all the connectionist paradigms considered could represent the stock indices behavior very accurately.