Influence of dietary spices and their active principles on pancreatic digestive enzymes in albino rats

A few common spices or their active principles were examined for their possible influence on digestive enzymes of pancreas in experimental rat. Groups of animals were maintained for 8 weeks on the following spice diets: curcumin (0.5%), capsaicin (15 mg%), piperine (20 mg%), ginger (50 mg%), cumin (1.25%), fenugreek (2%), mustard (250 mg%) and asafoetida (250 mg%). Dietary curcumin, capsaicin, piperine, ginger, fenugreek and asafoetida prominently enhanced pancreatic lipase activity. Curcumin, capsaicin, piperine, ginger, cumin and asafoetida also stimulated pancreatic amylase. Trypsin was significantly stimulated by curcumin, capsaicin, piperine, ginger and cumin, while chymotrypsin was stimulated by all the spices tested except mustard. This stimulatory influence of test spices on the pancreatic digestive enzymes was however not observed when their intake was restricted to a single oral dose. The positive influences on the pancreatic digestive enzymes exerted by a good number of spices consumed in diet could be a factor contributing to the well recognised digestive stimulant action of spices.     

Effects of curtailment on an admissions model for a graduate management program.

Developed 2 admissions models to predict future academic performance of graduate management students. The 1st model was based on 40 students who were admitted and enrolled in the program and was uncorrected for curtailment. The 2nd model was developed from the total applicant population of 222 students after curtailment correction. The corrected model demonstrated higher predictive validity than the uncorrected model for 2 future classes of students. Furthermore, different predictors entered each model, affecting the beta weights, validities of predictors, and the total amount of variance explained by the models. A factor analysis and an analysis of admissions decisions offer additional support for the curtailment-corrected model in selecting students with high academic potential. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Asymmetric membrane fiber-based carbon dioxide removal devices for ion chromatography

The application of hollow and filament-filled single asymmetric membrane fibers, consisting of a thin silicone layer on a tubular microporous support, for removing CO(2) in suppressed ion chromatography effluents is described. With appropriate choice of the removal device and operating conditions, the CO(2) can be essentially quantitatively (99+%) removed. For carbonate-based eluents, the use of such devices greatly reduces or eliminates the water dip, permitting better quantitation of poorly retained anions that elute close to the dip, allows practical gradient chromatography, and improves noise levels and attainable detection limits. In hydroxide eluent chromatography, the device largely removes the response from CO(2) present in the samples; this greatly aids atmospheric trace gas analysis by IC. Device dimensions are such that the dispersion introduced by the device is small.     

Gel permeation chromatography for characterization of graft copolymer

Summary The present paper describes the grafting of vinyl monomers onto cellulose nitrate in non-aqueous medium using benzoyl peroxide as a catalyst. The complete separation of the homopolymers and graft copolymer was carried out by selective solvent extraction. The graft copolymer was characterized by IR spectra. The GPC was used as a technique to differentiate between homopolymer, polymer mixture, polyblend, and graft copolymer.     

Transforming Binary Uncertainties for Robust Speech Recognition

Recently, several algorithms have been proposed to enhance noisy speech by estimating a binary mask that can be used to select those time-frequency regions of a noisy speech signal that contain more speech energy than noise energy. This binary mask encodes the uncertainty associated with enhanced speech in the linear spectral domain. The use of the cepstral transformation smears the information from the noise dominant time-frequency regions across all the cepstral features. We propose a supervised approach using regression trees to learn the nonlinear transformation of the uncertainty from the linear spectral domain to the cepstral domain. This uncertainty is used by a decoder that exploits the variance associated with the enhanced cepstral features to improve robust speech recognition. Systematic evaluations on a subset of the Aurora4 task using the estimated uncertainty show substantial improvement over the baseline performance across various noise conditions.     

Influence of Die Angle on Containerless Extrusion of Commercially Pure Titanium Tubes

Containerless tube extrusion has been investigated with commerically pure titanium at room temperature and a strain rate of 0.07 s^-1 using 20 conical dies of five different strains and four different angles with MoS₂ lubricant. Theoretical punch pressures have been calculated using appropriate equations from slab analysis of the process and compared with experimentally determined punch pressures. It is found that there exists an optimum angle at which the punch pressure is the least at a given strain.