Antioxidant Biosensor Using Microbe

The antioxidant compounds are needed for the food, beverages, and pharmaceuticals industry. For this purpose, an appropriate method is required to measure the antioxidant properties in various types of samples. Spectrophotometric method usually used has some weaknesses, including the high price, long sample preparation time, and less sensitivity. Among the alternative methods developed to overcome these weaknesses is antioxidant biosensor based on superoxide dismutase (SOD) enzyme. Therefore, this study was carried out to measure the SOD activity originating from Deinococcus radiodurans and to determine its kinetics properties. Carbon paste electrode modified with ferrocene and immobilized SOD exhibited anode and cathode current peak at potential of +400 and +300mv respectively, in both pure SOD and SOD of D. radiodurans. This indicated that the current generated was from superoxide catalytic dismutation reaction by SOD. Optimum conditions for SOD activity was at pH 9 and temperature of 27.50C for D. radiodurans SOD, and pH 11 and temperature of 200C for pure SOD. Dismutation reaction kinetics of superoxide catalyzed by SOD followed the Lineweaver-Burk kinetics with D. radiodurans SOD KMapp value was smaller than pure SOD. The result showed that D. radiodurans SOD had higher enzyme-substrate affinity and specificity than pure SOD. It concluded that D. radiodurans SOD had a great potential as biological recognition component for antioxidant biosensor.

Effect of Zeolite on the Decomposition Resistance of Organic Matter in Tropical Soils under Global Warming

Global temperature had increased by about 0.5oC over the past century, increasing temperature leads to a loss or a decrease of soil organic matter (SOM). Whereas soil organic matter in many tropical soils is less stable than that of temperate soils, and it will be easily affected by climate change. Therefore, conservation of soil organic matter is urgent issue nowadays. This paper presents the effect of different doses (5%, 15%) of Ca-type zeolite in conjunction with organic manure, applied to soil samples from Philippines, Paraguay and Japan, on the decomposition resistance of soil organic matter under high temperature. Results showed that a remain or slightly increase the C/N ratio of soil. There are an increase in percent of humic acid (PQ) that extracted with Na4P2O7. A decrease of percent of free humus (fH) after incubation was determined. A larger the relative color intensity (RF) value and a lower the color coefficient (6logK) value following increasing zeolite rates leading to a higher degrees of humification. The increase in the aromatic condensation of humic acid (HA) after incubation, as indicates by the decrease of H/C and O/C ratios of HA. This finding indicates that the use of zeolite could be beneficial with respect to SOM conservation under global warming condition.

Application of the Hybrid Methods to Solving Volterra Integro-Differential Equations

Beginning from the creator of integro-differential equations Volterra, many scientists have investigated these equations. Classic method for solving integro-differential equations is the quadratures method that is successfully applied up today. Unlike these methods, Makroglou applied hybrid methods that are modified and generalized in this paper and applied to the numerical solution of Volterra integro-differential equations. The way for defining the coefficients of the suggested method is also given.

A Modified Fuzzy C-Means Algorithm for Natural Data Exploration

In Data mining, Fuzzy clustering algorithms have demonstrated advantage over crisp clustering algorithms in dealing with the challenges posed by large collections of vague and uncertain natural data. This paper reviews concept of fuzzy logic and fuzzy clustering. The classical fuzzy c-means algorithm is presented and its limitations are highlighted. Based on the study of the fuzzy c-means algorithm and its extensions, we propose a modification to the cmeans algorithm to overcome the limitations of it in calculating the new cluster centers and in finding the membership values with natural data. The efficiency of the new modified method is demonstrated on real data collected for Bhutan-s Gross National Happiness (GNH) program.

Removal of Boron from Waste Waters by Ion- Exchange in a Batch System

Boron minerals are very useful for various industrial activities, such as glass industry and detergent industry, due to its mechanical and chemical properties. During the production of boron compounds, many of these are introduced into the environment in the form of waste. Boron is also an important micro nutrient for the plants to vegetate but if it exists in high concentrations, it could have toxic effects. The maximum boron level in drinking water for human health is given as 0.3 mg/L in World Health Organization (WHO) standards. The toxic effects of boron should be noted especially for dry regions, thus, in recent years, increasing attention has been paid to remove the boron from waste waters. In this study, boron removal is implemented by ion exchange process using Amberlite IRA-743 resin. Amberlite IRA-743 resin is a boron specific resin and it belongs to the polymerizate sorbent group within the aminopolyol functional group. Batch studies were performed to investigate the effects of various experimental parameters, such as adsorbent dose, initial concentration and pH, on the removal of boron. It is found that, when the adsorbent dose increases removal of boron from the liquid phase increases. However, an increase in the initial concentration decreases the removal of boron. The effective pH values for removal of boron are determined between 8.5 and 9. Equilibrium isotherms were also analyzed by Langmuir and Freundlich isotherm models. The Langmuir isotherm is obeyed better than the Freundlich isotherm.

Electroremediation of Cu-Contaminated Soil

This study investigated the removal efficiency of electrokinetic remediation of copper-contaminated soil at different combinations of enhancement reagents used as anolyte and catholyte. Sodium hydroxide (at 0.1, 0.5, and 1.0 M concentrations) and distilled water were used as anolyte, while lactic acid (at 0.01, 0.1, and 0.5 M concentrations), ammonium citrate (also at 0.01, 0.1, and 0.5 M concentrations) and distilled water were used as catholyte. A continuous voltage application (1.0 VDC/cm) was employed for 240 hours for each experiment. The copper content of the catholyte was determined at the end of the 240-hour period. Optimization was carried out with a Response Surface Methodology - Optimal Design, including F test, and multiple comparison method, to determine which pair of anolyte-catholyte was the most significant for the removal efficiency. "1.0 M NaOH" was found to be the most significant anolyte while it was established that lactic acid was the most significant type of catholyte to be used for the most successful electrokinetic experiments. Concentrations of lactic acid should be at the range of 0.1 M to 0.5 M to achieve maximum percent removal values.

Automatic Generation Control of Multi-Area Electric Energy Systems Using Modified GA

A modified Genetic Algorithm (GA) based optimal selection of parameters for Automatic Generation Control (AGC) of multi-area electric energy systems is proposed in this paper. Simulations on multi-area reheat thermal system with and without consideration of nonlinearity like governor dead band followed by 1% step load perturbation is performed to exemplify the optimum parameter search. In this proposed method, a modified Genetic Algorithm is proposed where one point crossover with modification is employed. Positional dependency in respect of crossing site helps to maintain diversity of search point as well as exploitation of already known optimum value. This makes a trade-off between exploration and exploitation of search space to find global optimum in less number of generations. The proposed GA along with decomposition technique as developed has been used to obtain the optimum megawatt frequency control of multi-area electric energy systems. Time-domain simulations are conducted with trapezoidal integration along with decomposition technique. The superiority of the proposed method over existing one is verified from simulations and comparisons.

Comparison of The Fertilizer Properties of Ash Fractions from Medium-Sized (32 MW) and Small-Sized (6 MW) Municipal District Heating Plants

Due to the low heavy metal concentrations, the bottom ash from a 32 MW municipal district heating plant was determined to be a potential forest fertilizer as such. However, additional Ca would be needed, because its Ca concentration of 1.9- % (d.w.) was lower than the statutory Finnish minimum limit value of 6.0-% (d.w.) for Ca in forest fertilizer. Due to the elevated As concentration (53.0 mg/kg; d.w.) in the fly ash from the 32 MW municipal district heating plant, and Cr concentration (620 mg/kg; d.w.) in the ash fraction (i.e. mixture of the bottom ash and fly ash) from the 6 MW municipal district heating plant, which exceed the limit values of 30 mg/kg (d.w.) and 300 mg/kg (d.w.) for As and Cr, respectively, these residues are not suitable as forest fertilizers. Although these ash fractions cannot be used as a forest fertilizer as such, they can be used for the landscaping of landfills or in industrial and other areas that are closed to the public. However, an environmental permit is then needed.

Evaluating Spectral Relationships between Signals by Removing the Contribution of a Common, Periodic Source A Partial Coherence-based Approach

Partial coherence between two signals removing the contribution of a periodic, deterministic signal is proposed for evaluating the interrelationship in multivariate systems. The estimator expression was derived and shown to be independent of such periodic signal. Simulations were used for obtaining its critical value, which were found to be the same as those for Gaussian signals, as well as for evaluating the technique. An Illustration with eletroencephalografic (EEG) signals during photic stimulation is also provided. The application of the proposed technique in both simulation and real EEG data indicate that it seems to be very specific in removing the contribution of periodic sources. The estimate independence of the periodic signal may widen partial coherence application to signal analysis, since it could be used together with simple coherence to test for contamination in signals by a common, periodic noise source.

Seismic Control of Tall Building Using a New Optimum Controller Based on GA

This paper emphasizes on the application of genetic algorithm (GA) to optimize the parameters of the TMD for achieving the best results in the reduction of the building response under earthquake excitations. The Integral of the Time multiplied Absolute value of the Error (ITAE) based on relative displacement of all floors in the building is taken as a performance index of the optimization criterion. The problem of robustly TMD controller design is formatted as an optimization problem based on the ITAE performance index to be solved using GA that has a story ability to find the most optimistic results. An 11–story realistic building, located in the city of Rasht, Iran is considered as a test system to demonstrate effectiveness of the proposed GA based TMD (GATMD) controller without specifying which mode should be controlled. The results of the proposed GATMD controller are compared with the uncontrolled structure through timedomain simulation and some performance indices. The results analysis reveals that the designed GA based TMD controller has an excellent capability in reduction of the seismically excited example building and the ITAE performance, that is so for remains as unknown, can be introduced a new criteria - method for structural dynamic design.

The Development of Taiwanese Electronic Medical Record Systems Evaluation Instrument

This study used Item Analysis, Exploratory Factor Analysis (EFA) and Reliability Analysis (Cronbach-s α value) to exam the Questions which selected by the Delphi method based on the issue of “Socio-technical system (STS)" and user-centered perspective. A structure questionnaire with seventy-four questions which could be categorized into nine dimensions (healthcare environment, organization behaviour, system quality, medical data quality, service quality, safety quality, user usage, user satisfaction, and organization net benefits) was provided to evaluate EMR of the Taiwanese healthcare environment.

Predicting the Three Major Dimensions of the Learner-s Emotions from Brainwaves

This paper investigates how the use of machine learning techniques can significantly predict the three major dimensions of learner-s emotions (pleasure, arousal and dominance) from brainwaves. This study has adopted an experimentation in which participants were exposed to a set of pictures from the International Affective Picture System (IAPS) while their electrical brain activity was recorded with an electroencephalogram (EEG). The pictures were already rated in a previous study via the affective rating system Self-Assessment Manikin (SAM) to assess the three dimensions of pleasure, arousal, and dominance. For each picture, we took the mean of these values for all subjects used in this previous study and associated them to the recorded brainwaves of the participants in our study. Correlation and regression analyses confirmed the hypothesis that brainwave measures could significantly predict emotional dimensions. This can be very useful in the case of impassive, taciturn or disabled learners. Standard classification techniques were used to assess the reliability of the automatic detection of learners- three major dimensions from the brainwaves. We discuss the results and the pertinence of such a method to assess learner-s emotions and integrate it into a brainwavesensing Intelligent Tutoring System.

Classifier Combination Approach in Motion Imagery Signals Processing for Brain Computer Interface

In this study we focus on improvement performance of a cue based Motor Imagery Brain Computer Interface (BCI). For this purpose, data fusion approach is used on results of different classifiers to make the best decision. At first step Distinction Sensitive Learning Vector Quantization method is used as a feature selection method to determine most informative frequencies in recorded signals and its performance is evaluated by frequency search method. Then informative features are extracted by packet wavelet transform. In next step 5 different types of classification methods are applied. The methodologies are tested on BCI Competition II dataset III, the best obtained accuracy is 85% and the best kappa value is 0.8. At final step ordered weighted averaging (OWA) method is used to provide a proper aggregation classifiers outputs. Using OWA enhanced system accuracy to 95% and kappa value to 0.9. Applying OWA just uses 50 milliseconds for performing calculation.

Applying Fuzzy FP-Growth to Mine Fuzzy Association Rules

In data mining, the association rules are used to find for the associations between the different items of the transactions database. As the data collected and stored, rules of value can be found through association rules, which can be applied to help managers execute marketing strategies and establish sound market frameworks. This paper aims to use Fuzzy Frequent Pattern growth (FFP-growth) to derive from fuzzy association rules. At first, we apply fuzzy partition methods and decide a membership function of quantitative value for each transaction item. Next, we implement FFP-growth to deal with the process of data mining. In addition, in order to understand the impact of Apriori algorithm and FFP-growth algorithm on the execution time and the number of generated association rules, the experiment will be performed by using different sizes of databases and thresholds. Lastly, the experiment results show FFPgrowth algorithm is more efficient than other existing methods.

Effect of Shallow Groundwater Table on the Moisture Depletion Pattern in Crop Root Zone

Different techniques for estimating seasonal water use from soil profile water depletion frequently do not account for flux below the root zone. Shallow water table contribution to supply crop water use may be important in arid and semi-arid regions. Development of predictive root uptake models, under influence of shallow water table makes it possible for planners to incorporate interaction between water table and root zone into design of irrigation projects. A model for obtaining soil moisture depletion from root zone and water movement below it is discussed with the objective to determine impact of shallow water table on seasonal moisture depletion patterns under water table depth variation, up to the bottom of root zone. The role of different boundary conditions has also been considered. Three crops: Wheat (Triticum aestivum), Corn (Zea mays) and Potato (Solanum tuberosum), common in arid & semi-arid regions, are chosen for the study. Using experimentally obtained soil moisture depletion values for potential soil moisture conditions, moisture depletion patterns using a non linear root uptake model have been obtained for different water table depths. Comparative analysis of the moisture depletion patterns under these conditions show a wide difference in percent depletion from different layers of root zone particularly top and bottom layers with middle layers showing insignificant variation in moisture depletion values. Moisture depletion in top layer, when the water table rises to root zone increases by 19.7%, 22.9% & 28.2%, whereas decrease in bottom layer is 68.8%, 61.6% & 64.9% in case of wheat, corn & potato respectively. The paper also discusses the causes and consequences of increase in moisture depletion from top layers and exceptionally high reduction in bottom layer, and the possible remedies for the same. The numerical model developed for the study can be used to help formulating irrigation strategies for areas where shallow groundwater of questionable quality is an option for crop production.

Comprehensive Evaluation on China-s Industrial Structure Optimization from the Perspective of Coordination

From the perspective of industrial structure coordination and based on an explicit definition for the connotation of industrial structure coordination, the synergetic coefficients are used to measure the coordination degree between three industries' input structure and output structure, and then the efficacy function method is employed to comprehensively evaluate the level of China-s industrial structure optimization. It is showed that Chinese industrial structure presented a "v-shaped" variation tendency between 1996 and 2008, and its industrial structure adjustment got obvious achievements after 2003, with the industrial structure optimization level increasing continuously. However in 2009, the level of China-s industrial structure optimization declined sharply due to the decreasing contribution degree of value added structure and energy structure coordination and the lower coordination degree of value added structure and capital structure.

Research of a Multistep Method Applied to Numerical Solution of Volterra Integro-Differential Equation

Solution of some practical problems is reduced to the solution of the integro-differential equations. But for the numerical solution of such equations basically quadrature methods or its combination with multistep or one-step methods are used. The quadrature methods basically is applied to calculation of the integral participating in right hand side of integro-differential equations. As this integral is of Volterra type, it is obvious that at replacement with its integrated sum the upper limit of the sum depends on a current point in which values of the integral are defined. Thus we receive the integrated sum with variable boundary, to work with is hardly. Therefore multistep method with the constant coefficients, which is free from noted lack and gives the way for finding it-s coefficients is present.

Molecular Dynamic Simulation and Receptor-based Pharmacophore Modeling on Human Renin for Discovery of Novel Inhibitors

Hypertension is characterized with stress on the heart and blood vessels thus increasing the risk of heart attack and renal diseases. The Renin angiotensin system (RAS) plays a major role in blood pressure control. Renin is the enzyme that controls the RAS at the rate-limiting step. Our aim is to develop new drug-like leads which can inhibit renin and thereby emerge as therapeutics for hypertension. To achieve this, molecular dynamics (MD) simulation and receptor-based pharmacophore modeling were implemented, and three rennin-inhibitor complex structures were selected based on IC50 value and scaffolds of inhibitors. Three pharmacophore models were generated considering conformations induced by inhibitor. The compounds mapped to these models were selected and subjected to drug-like screening. The identified hits were docked into the active site of renin. Finally, hit1 satisfying the binding mode and interaction energy was selected as possible lead candidate to be used in novel renin inhibitors.

Image Restoration in Non-Linear Filtering Domain using MDB approach

This paper proposes a new technique based on nonlinear Minmax Detector Based (MDB) filter for image restoration. The aim of image enhancement is to reconstruct the true image from the corrupted image. The process of image acquisition frequently leads to degradation and the quality of the digitized image becomes inferior to the original image. Image degradation can be due to the addition of different types of noise in the original image. Image noise can be modeled of many types and impulse noise is one of them. Impulse noise generates pixels with gray value not consistent with their local neighborhood. It appears as a sprinkle of both light and dark or only light spots in the image. Filtering is a technique for enhancing the image. Linear filter is the filtering in which the value of an output pixel is a linear combination of neighborhood values, which can produce blur in the image. Thus a variety of smoothing techniques have been developed that are non linear. Median filter is the one of the most popular non-linear filter. When considering a small neighborhood it is highly efficient but for large window and in case of high noise it gives rise to more blurring to image. The Centre Weighted Mean (CWM) filter has got a better average performance over the median filter. However the original pixel corrupted and noise reduction is substantial under high noise condition. Hence this technique has also blurring affect on the image. To illustrate the superiority of the proposed approach, the proposed new scheme has been simulated along with the standard ones and various restored performance measures have been compared.

Simultaneously Reduction of NOx and Soot Emissions in a DI Heavy Duty diesel Engine Operating at High Cooled EGR Rates

One promising way to achieve low temperature combustion regime is the use of a large amount of cooled EGR. In this paper, the effect of injection timing on low temperature combustion process and emissions were investigated via three dimensional computational fluid dynamics (CFD) procedures in a DI diesel engine using high EGR rates. The results show when increasing EGR from low levels to levels corresponding to reduced temperature combustion, soot emission after first increasing, is decreased beyond 40% EGR and get the lowest value at 58% EGR rate. Soot and NOx emissions are simultaneously decreased at advanced injection timing before 20.5 ºCA BTDC in conjunction with 58% cooled EGR rate in compared to baseline case.