LINAMARASE: IMMOBILIZATION OF A CRUDE ENZYME

ABSTRACT Linamarase from cassava cortex was immobilized on polyacrylamide gel. A crude extract of the enzyme containing most of the intracellular proteins was used for the technique to simulate the enzyme in cassava. Immobilization of the enzyme increased the Michaelis constants for all substrates when compared with the native enzyme. Both free and immobilized linamarase hydrolyzed p-nitrophenylβ D-glucoside, linamarin and p-nitrophenylβ-D-galactoside. The immobilized enzyme was more stable than the free enzyme at room temperature (25C) and 41C. Both forms gave a bell-shaped curve with maximal activity at pH 6.0; these data indicated two catalytic ionizable residues with pK_a 5.7 and pK_a 6.5.     

基于EM和贝叶斯网络的丢失数据填充算法

实际应用中存在大量的丢失数据的数据集,对丢失数据的处理已成为目前分类领域的研究热点。分析和比较了几种通用的丢失数据填充算法,并提出一种新的基于EM和贝叶斯网络的丢失数据填充算法。算法利用朴素贝叶斯估计出EM算法初值,然后将EM和贝叶斯网络结合进行迭代确定最终更新器,同时得到填充后的完整数据集。实验结果表明,与经典填充算法相比,新算法具有更高的分类准确率,且节省了大量开销。     

Discharge Plasma Assisted Adsorbents for Exhaust Treatment： A Comparative Analysis on Enhancing NOx Removal

An analysis has been made on the discharge plasma coupled with an adsorbent system for NOx removal. The cascaded plasma-adsorbent system may be perceived as a better alternative for the existing adsorbent-based abatement system in the industry. In this study the exhaust is sourced from a diesel generator set. It was observed that better NO removal in a plasma reactor can be made possible by achieving higher average fields and subsequent NO2 removal can be improved using an adsorbent system connected in cascade with the plasma system. The paper describes various findings pertaining to these comparative analyses.     

Fuzzy clustering and Whale-based neural network to food recognition and calorie estimation for daily dietary assessment

The calorie value of the food items taken by the person in everyday life needs to be monitored to reduce the risk of obesity, heart problems, and diabetes, etc. The calorie estimator in the existing models has reduced accuracy since the calorie value of each food varies with mass. This paper introduces a dietary assessment system based on the proposed Cauchy, Generalized T-Student, and Wavelet kernel based Wu-and-Li Index Fuzzy clustering (CSW-WLIFC) based segmentation and the proposed Whale Levenberg Marquardt Neural Network (WLM-NN) classifier. The proposed CSW-WLIFC based segmentation segments the image based on the existing WLI-FC algorithm. A novel CSW based kernel function is utilized in the segmentation process. Feature vectors such as color, shape, and texture are extracted from the segmented image. The Neural Network is trained with the Whale-Levenberg Marquardt (WLM) model to recognize each food item from the tray image. The proposed calorie estimator calculates the calorie value of each food item. From the simulation results, it is evident that the proposed model has the improved performance than the existing models with the values of 0.999, 0.9643, 0.9627, and 0.0184 for the segmentation accuracy, macro average accuracy, standard accuracy, mean square error, respectively.     

Improved robust performance bounds in covariance majorant analysis

Over the past decade, a considerable amount of attention has been devoted to the subject of robustness analysis. However, the current literature on robustness analysis concentrates largely on the qualitative issue of robust stability. To date, very few results have been developed for the quantitative issue of robust performance. An exception to this is the recent work of Hyland and Bernstein (1987) in covariance majorant analysis. This work developed bounds on cost functions which can represent the variances of selected system variables. This paper presents improvements in covariance majorant analysis. Specifically, less conservative (i.e., smaller) upper bounds are developed for the cost functions. Lower cost bounds are also developed.     

PROCESSING AND ACCEPTABILITY OF FRIED CASSAVA BALLS ("AKARA-AKPU") SUPPLEMENTED WITH MELON AND SOYBEAN FLOURS

The processing and acceptability of fried cassava balls (“Akara‐akpu”) supplemented with melon and soybean flours were studied. Cassava flour, defatted soybean flour and cassava mash were produced. Some functional and chemical properties of the flours were determined. Akara‐akpu prepared from 100% cassava mash served as control; 100% cassava flour, 80% cassava flour + 20% defatted soybean and 70% cassava flour + 30% defatted melon flour were prepared. Akara‐akpu balls were subjected to chemical and physical analyses. Akara‐akpu prepared from composite flour blends had higher protein, fat, ash and energy value than Akara‐akpu from 100% cassava mash. The cyanide content and degree of starch gelatinization of Akara‐akpu prepared from 100% cassava mash (control) were higher than Akara‐akpu prepared from cassava mash plus composite flour blends. There was a significant difference (P ≤ 0.05) in weight and yield between Akara‐akpu prepared from 100% cassava mash (control) and cassava mash plus composite flour blends. There was no significant difference (P ≤ 0.05) in volume between Akara‐akpu made from control sample and those cassava plus composite flour blends.