Antioxidant and antidiabetic properties of condensed tannins in acetonic extract of selected raw and processed indigenous food ingredients from Kenya

Recently, tannins have received considerable attention as health-promoting component in various plant foods and several studies have reported on its nutraceutical properties. However, no study has established the role of condensed tannins in indigenous foods of Kenya. Therefore, this study was designed to evaluate the antioxidant activity (DPPH and FRAP) and antidiabetic effects (α-amylase and α-glucosidase inhibition activities) of condensed tannins in some selected raw and traditionally processed indigenous cereals, legumes, oil seeds, and vegetables. The condensed tannin content of the grains and vegetables ranged between 2.55 and 4.35 g/100 g DM and 1.53 and 5.73 g/100 g DM, respectively. The scavenging effect of acetonic extract on DPPH radical ranged from 77% to 90% while the reducing power was found to be 31 to 574 mmol Fe(II)/g DM in all the investigated food ingredients. The condensed tannin extracts of the analyzed samples showed promising antidiabetic effects with potential α-amylase and α-glucosidase inhibition activities of 23% to 44% and 58% to 88%, respectively. Condensed tannins extracted from the amaranth grain, finger millet, field bean, sunflower seeds, drumstick, and amaranth leaves exerted significantly higher antioxidant and antidiabetic activities than other food ingredients. Among the traditional processing methods, roasting of grains and cooking of vegetables were found to be more suitable mild treatments for preserving the tannin compound and its functional properties as opposed to soaking + cooking and blanching treatments. The identified elite sources of optimally processed indigenous food ingredients with promising results could be used as health-promoting ingredients through formulation of therapeutic diets.     

GAS HOLDUP AND HEAT TRANSFER FROM IMMERSED SURFACES IN TWO- AND THREE-PHASE SYSTEMS IN BUBBLE COLUMNS

Two experimental slurry bubble column facilities comprising of 10.8 and 30.5 cm diameter columns and appropriate for conducting hydrodynamic and heat transfer studies are described. The average and local gas holdup data are reported for the air-water system as a function of air velocity. The holdups for the three phases are also reported for the air-water-glass beads system over a range of air velocity values. The air holdup data are compared with the predictions of some of the commonly used correlations. The heat transfer coefficient for a 19 mm diameter cylindrical probe and the two- and three-phase dispersions are measured as a function of air velocity. Most of these hydrodynamic and heat transfer data correspond to the churn turbulent regime and the values obtained on the two columns differ appreciably from each other under similar operating conditions. This fact indicates that the scaleup of slurry bubble columns could be quite difficult on the basis of data obtained on the bench and pilot-plant scale units. The continuing data from these facilities on different systems will shed more light in the future on this important aspect which is crucial to the commercialization of indirect coal liquefaction technology.     

Photoluminescence properties of nanocrystalline ZnS on nanoporous silicon

This paper embodies the report on the microwave solvothermal synthesizing of nanocrystalline ZnS particles for optoelectronic device. The effect of different parameters such as time, temperature, solvents, molar ratio of zinc and thiourea on the phase(s) formation of nanocrystalline Zinc Sulphide was investigated. The obtained nanosize ZnS materials were characterized by the X-ray diffraction, Optical absorption measurements, TEM and Photoluminescence studies. The crystallite size of the ZnS nanoparticles was estimated from the X-ray diffraction pattern by using Scherrer's formula. The as prepared material was obtained in the cubic phase, which showed a perfect match with the earlier reports. The Optical absorption edge of ZnS were blue shifted from the absorption edge of bulk ZnS. The estimated band gap value of ZnS was 4.01 eV. The ZnS nano materials were coated on nano porous silicon by screen-printing technique. Luminescence studies indicated room temperature emission in the wavelength ranges from 422.6 to 612 nm, which cover the blue emission to red emission. The emitted light that depending on the created pore size from porous silicon and the size of the ZnS nano particles.     

Recognition of human actions using CNN-GWO: a novel modeling of CNN for enhancement of classification performance

Recognizing human actions from unconstrained videos turns to be a major challenging task in computer visualization approaches due to decreased accuracy in the feature classification performance. Therefore to improve the classification performance it is essential to minimize the ‘classification’ errors. Here, in this work, we propose a hybrid CNN-GWO approach for the recognition of human actions from the unconstrained videos. The weight initializations for the proposed deep Convolutional Neural Network (CNN) classifiers highly depend on the generated solutions of GWO (Grey Wolf Optimization) algorithm, which in turn minimizes the ‘classification’ errors. The action bank and local spatio-temporal features are generated for a video and fed into the ‘CNN’ classifiers. The ‘CNN’ classifiers are trained by a gradient descent algorithm to detect a ‘local minimum’ during the fitness computation of GWO ‘search agents’. The GWO algorithms ‘global search’ capability as well as the gradient descent algorithms ‘local search’ capabilities are subjected for the identification of a solution which is nearer to the global optimum. Finally, the classification performance can be further enhanced by fusing the classifiers evidences produced by the GWO algorithm. The proposed classification frameworks efficiency for the recognition of human actions is evaluated with the help of four achievable action recognition datasets namely HMDB51, UCF50, Olympic Sports and Virat Release 2.0. The experimental validation of our proposed approach shows better achievable results on the recognition of human actions with 99.9% recognition accuracy.     

Robust <Emphasis Type="Italic">H</Emphasis><Subscript>∞</Subscript> Performance of Discrete-time Neural Networks with Uncertainty and Time-varying Delay

In this paper, we are concerned with the robust H_∞ problem for a class of discrete-time neural networks with uncertainties. Under a weak assumption on the activation functional, some novel summation inequality techniques and using a new Lyapunov-Krasovskii (L-K) functional, a delay-dependent condition guaranteeing the robust asymptotically stability of the concerned neural networks is obtained in terms of a Linear Matrix Inequality(LMI). It is shown that this stability condition is less conservative than some previous ones in the literature. The controller gains can be derived by solving a set of LMIs. Finally, two numerical examples result are given to illustrate the effectiveness of the developed theoretical results.     

Event Pattern Analysis and Prediction at Sentence Level using Neuro-Fuzzy Model for Crime Event Detection

Classifying the sentences that describe Events is an important task for many applications. In this paper, Event patterns are identified and extracted at sentence level using term features. The terms that trigger Events along with the sentences are extracted from web documents. The sentence structures are analyzed using POS tags. A hierarchal sentence classification model is proposed by considering specific term features of the sentence and the rules are derived. The rules fail to define a clear boundary between the patterns and create ambiguity and impreciseness. To overcome this, suitable fuzzy rules are derived which gives importance to all term features of the sentence. The fuzzy rules are constructed with more variables and generate sixteen patterns. Artificial Neuro-Fuzzy Inference System (ANFIS) model is proposed for training and classifying the sentence patterns for capturing the knowledge present in sentences. The obtained patterns are assigned linguistic grades based on previous classification knowledge. These grades represent the type and quality of information in the patterns. The membership function is used to evaluate the fuzzy rules. The patterns share the membership values between [0–1] which determines the weights for each pattern. Later, higher weighted patterns are considered to build Event Corpus, which helps in retrieving useful and interested information of Event Instances. The performance of the proposed approach classification is evaluated for ‘Crime’ Event by crawling documents from WWW and also evaluated for benchmark dataset for ‘Die’ Event. It is found that the performance of the proposed approach is encouraging when compared with recently proposed similar approaches.     

Spray-Deposited Rare Earth Metal Ions (La3+ and Sm3+) Substituted CoFe2O4 Thin Films for NH3 Gas-Sensing Applications

Journal of Superconductivity and Novel Magnetism - We report here the NH3 gas-sensing properties of homemade spray deposited pristine and different concentrations of La3+ and Sm3+ ions substituted...     

Total phenolic content,antioxidant activity,and type II diabetes related functionality of traditionally processed ox-eye bean [Mucuna gigantea (Willd) DC.] seeds: An Indian underutilized food legume

The methanolic extract of ox-eye bean [Mucuna gigantea (Willd) DC.] contained total free phenolic content of 14.80±1.28 g catechin equivalent/100 g extract dry matter. Encouraging levels of ferric reducing/antioxidant power (FRAP, 1,023 mmol Fe[II]/mg extract), inhibition of β-carotene degradation (59.35%) and radical scavenging activity against DPPH (72.12%) and superoxide (43.11%) were exhibited by the raw samples. Further, it also recorded 82.17% of α-amylase and 91.26% of α-glucosidase enzyme inhibition characteristics. Sprouting+oil-frying caused a apparent increase on the total free phenolic content and also significant improvement on the antioxidant and free radical scavenging capacity of methanolic extract, while soaking+cooking as well as open-pan roasting treatments showed diminishing effects. Moreover, inhibition of α-amylase and α-glucosidase enzyme activities was declined to 22.82 and 45.47%, respectively during sprouting+oilfrying treatment, which are more desirable for the dietary management of type II diabetic patients.     

Interval graph of facial regions with common intersection salient points for identifying and classifying facial expression

Multimedia Tools and Applications - Measuring the facial expression is an important research and used in many real-time applications. Various methods are proposed in the academia and industry for a...