Nutritional quality of detoxified karanja (Pongamia glabra) oil

Fatty acid composition of crude karanja (Pongamia glabra) oil resembles groundnut oil but it contains some toxic phenolic compounds, like karanjin and pongamol. Removal of these phenolic compounds prior to edible use is therefore important. Nutritional quality of the refined karanja oil (detoxified by isopropanol extraction, bleaching and deodorization) has been investigated in rats by feeding this oil where groundnut oil has been used as control. These two oils were fed at a 20% level in each group in an 18% protein and 55% starch diet for six weeks. The refined karanja oil was observed to be utilized in an identical manner to that of groundnut oil as revealed by growth of rats, food efficiency ratio and the lipid profile of serum and liver tissues.     

Algorithms for robust identification in ℋ∞ with nonuniformly spaced frequency response data

In this paper, first a two-stage robustly covergent identification algorithm in ℋ_∞ for nonuniformly spaced data is proposed. The worst-case error of the algorithm converges to zero faster than polynomial rates in the noise-free case when the identified system is an exponentially stable discrete-time system. The algorithm is characterized by a rational interpolation step with fixed poles at zero and infinity. Next, a minimax algorithm with better convergence properties is introduced. Sensitivity of the algorithms to small variations in the frequency values is also studied.     

On the worst-case divergence of the least-squares algorithm

In this paper, we provide a _∞-norm lower bound on the worst-case identification error of least-squares estimation when using FIR model structures. This bound increases as a logarithmic function of model complexity and is valid for a wide class of inputs characterized as being quasi-stationary with covariance function falling off sufficiently quickly.     

Comparison of the effects of various presettings on the colour of polyamide 6.6 dyed with acid dyestuffs

Polymeric fibres are semicrystalline structures in which the macromolecules are rarely oriented in their equilibrium state. Further instabilities are imparted when the fibres are converted to yarns and the yarns to fabrics. Heat-setting is an important industrial process, as it reduces the fibre strain to an acceptable limit. This paper presents results of a study on the effects of various presettings (heat-, steam- and hot water-setting processes) on the dyeing properties of polyamide 6.6 fibres with acid dyestuffs. It was found that the colour yield is lower for dyed samples after dry heat-setting, but in the case of samples that have been hot water-set or steam-set, the colour yield increases slightly for light shades and remains constant for dark shades, compared with the unset dyed sample.     

The least squares algorithm, parametric system identification and bounded noise

The least squares parametric system identification algorithm is analyzed assuming that the noise is a bounded signal. A bound on the worst-case parameter estimation error is derived. This bound shows that the worst-case parameter estimation error decreases to zero as the bound on the noise is decreased to zero.     

Optimizing the Matrix Multiplication Using Strassen and Winograd Algorithms with Limited Recursions on Many-Core

Many-core systems are basically designed for applications having large data parallelism. We propose an efficient hybrid matrix multiplication implementation based on Strassen and Winograd algorithms (S-MM and W-MM) on many-core. A depth first (DFS) traversal of a recursion tree is used where all cores work in parallel on computing each of the \(N \times N\) sub-matrices, which are computed in sequence. DFS reduces the storage to the detriment of large data motion to gather and aggregate the results. The proposed approach uses three optimizations: (1) a small set of basic algebra functions to reduce overhead, (2) invoking efficient library (CUBLAS 5.5) for basic functions, and (3) using parameter-tuning of parametric kernel to improve resource occupancy. Evaluation of S-MM and W-MM is carried out on GPU and MIC (Xeon Phi). For GPU, W-MM and S-MM with one recursion level outperform CUBLAS 5.5 Library with up to twice as fast for arrays satisfying \(N \ge 2048\) and \(N \ge 3072\), respectively. Similar trends are observed for S-MM with reordering (R-S-MM), which is used to save storage. Compared to NVIDIA SDK library, S-MM and W-MM achieved a speedup between 20\(\times \) and 80\(\times \) for the above arrays. For MIC, two-recursion S-MM with reordering is faster than MKL library by 14–26 % for \(N \ge 1024\). Proposed implementations achieve 2.35 TFLOPS (67 % of peak) on GPU and 0.5 TFLOPS (21 % of peak) on MIC. Similar encouraging results are obtained for a 16-core Xeon-E5 server. We conclude that S-MM and W-MM implementations with a few recursion levels can be used to further optimize the performance of basic algebra libraries.     

Role of Genetic Factors in Vascular Access Thrombosis in Hemodialysis Patients

Vascular access thrombosis is a frequent complication in hemodialysis (HD) patients. Genetic mutations, inflammation, and changes in the vascular wall are some factors that are thought to increase thrombosis risk. In this study, we tested for possible relationships between vascular thrombosis and some known thrombophilic mutation/polymorphisms in coagulation factors [factor V Leiden (FVL), prothrombin (Pt) G20210A, methylene tetrahydrofolate reductase (MTHFR C677T), factor XIII (F-XIII) Val34Leu, alpha-fibrinogen (AF) Thr312Ala, factor VII (F-VII) R353Q] and angiotensin I converting enzyme (ACE) gene in our HD patients. Patients who had experienced at least 3 episodes of AVF thrombosis composed of the study group, and patients who had never encountered this complication composed of the control group. None of the patients in either group had a history of diabetes mellitus, atherosclerosis, dialysis-related amyloidosis, or vasculitis. In order to find the frequency of F-XIII Val34Leu, AF Thr312Ala, and F-VII R353Q polymorphisms in our population, we also searched persons without renal disease or history of thrombosis (normal group). Results are summarized in Table. There was a tendency toward thrombotic mutation/polymorphisms in the study group for FVL, Pt G20210A, ACE I/D, and AF Thr312Ala. We suggest that patients who develop recurrent AVF thrombosis should be screened for the above-mentioned factors and investigated for other possible risk factors. This screening would allow more effective focus on prophylaxis.  

     

Classifier subset selection for biomedical named entity recognition

Classifier ensembling approach is considered for biomedical named entity recognition task. A vote-based classifier selection scheme having an intermediate level of search complexity between static classifier selection and real-valued and class-dependent weighting approaches is developed. Assuming that the reliability of the predictions of each classifier differs among classes, the proposed approach is based on selection of the classifiers by taking into account their individual votes. A wide set of classifiers, each based on a different set of features and modeling parameter setting are generated for this purpose. A genetic algorithm is developed so as to label the predictions of these classifiers as reliable or not. During testing, the votes that are labeled as being reliable are combined using weighted majority voting. The classifier ensemble formed by the proposed scheme surpasses the full object F-score of the best individual classifier by 2.75% and it is the highest score achieved on the data set considered.     

Radionuclide concentration in tea, cabbage, orange, kiwi and soil and lifetime cancer risk due to gamma radioactivity in Rize, Turkey

BACKGROUND: In this study, the activity concentrations of ²³²Th, ²³⁸U, ⁴⁰K and ¹³⁷Cs were measured in tea, cabbage, orange, kiwi and soil samples collected from different stations using gamma spectrometry with a high‐purity germanium detector. RESULTS: The average activity concentrations of ²³²Th, ²³⁸U, ⁴⁰K and ¹³⁷Cs were found to be 8.2 ± 1.8, 17.3 ± 3.3, 465.8 ± 11.8 and 20.9 ± 3.8 Bq kg^?1 in food samples, and 72.4 ± 9.8, 51.1 ± 8.3, 229.3 ± 14.7 and 312.9 ± 11.5 Bq kg^?1 in farm soils, respectively. The internal effective dose to individuals and excess lifetime cancer risk from the consumption of the food type radioactivity ranged between 11.7 and 53.6 µSv y^?1 and between 0.05 × 10^?3 and 0.24 × 10^?3, respectively. The annual external gamma effective dose and excess lifetime cancer risk in the farms due to soil radioactivity ranged between 94.1 and 139.8 µSv y^?1 and between 0.43 × 10^?3 and 0.64 × 10^?3, respectively. The mean transfer factors of ²³²Th, ²³⁸U, ⁴⁰K and ¹³⁷Cs, from the soil to vegetables and fruit were 0.57, 0.32, 2.12 and 0.04, respectively. CONCLUSION: Annual effective gamma doses were found to be higher than the world's average in soil samples. The excess lifetime cancer risks were only found higher than the world's average in soil samples. Copyright © 2011 Society of Chemical Industry     

Radioactivity and heavy metal concentrations in food samples from Rize, Turkey

BACKGROUND: Rize in Turkey was contaminated by the Chernobyl accident in 1986. A comprehensive study was planned and carried out to determine the radioactivity levels and heavy metal concentrations in four food categories collected in Rize in 2008, 2009 and 2010. RESULTS: Tomato showed the highest concentration of ²³⁸U, at 9.43 ± 0.128 Bq kg^?1, whereas the lowest concentration of 0.20 ± 0.02 Bq kg^?1 was measured in aubergine samples. The highest concentration of ²³²Th was measured at 3.22 ± 0.29 Bq kg^?1 in grape samples. ⁴⁰K was found to contribute the highest activity in all the food samples. The highest activity concentration of ¹³⁷Cs was 10.20 ± 4.19 Bq kg^?1, for parsley. The average contribution range of each of the heavy metals to the dietary intake was 0.13–9.14, 0.27–34.63, 0.05–3.62, 0.11–14.97, 0.78–8.51 and 0.01–1.57 mg, respectively, for Mn, Fe, Cu, Zn, Ni and As. CONCLUSION: The range of radioactivity levels in food samples of the present study is of no risk to public health. Heavy metal concentrations of Mn, Fe, Cu, Zn, Ni and As obtained were far below the established values by FAO/WHO limits. Copyright © 2011 Society of Chemical Industry