A Review In Preparation of Electronic Ink for Electrophoretic Displays

Electrophoretic displays attracted a lot of attention recently due to its low cost, low weight, low power consumption and reliability. Based on these characteristics, they are going to replace the conventional paper. Electrophoretic displays are called non- emitting displays based on light particle suspensions. They behave as motion of charged particles in a dielectric fluid towards the electrodes with the opposite charge. Electrical and optical properties of electrophoretic displays suspension composition are dependent on the electronic ink that is called E- ink. Thus, key factors in determining image quality depended on electrophoretic particle properties. Enhancing the great image quality for accurate image control and faster response to the voltage applied is dependent on the very small particle size, narrow size distribution and high surface charge of particles. So a lot of research has been done on the modification of particles, surface morphology, surface charge and their stability in media. Therefore, this article reviews the studies of these topics

A Review In Preparation of Electronic Ink for Electrophoretic Displays

Electrophoretic displays attracted a lot of attention recently due to its low cost, low weight, low power consumption and reliability. Based on these characteristics, they are going to replace the conventional paper. Electrophoretic displays are called non- emitting displays based on light particle suspensions. They behave as motion of charged particles in a dielectric fluid towards the electrodes with the opposite charge. Electrical and optical properties of electrophoretic displays suspension composition are dependent on the electronic ink that is called E- ink. Thus, key factors in determining image quality depended on electrophoretic particle properties. Enhancing the great image quality for accurate image control and faster response to the voltage applied is dependent on the very small particle size, narrow size distribution and high surface charge of particles. So a lot of research has been done on the modification of particles, surface morphology, surface charge and their stability in media. Therefore, this article reviews the studies of these topics

Correlation and path-cofficient analysis of seed yield and yield related trait in Iranian confectionery sunflower populations

This study was undertaken in order to determine the association among yield components and their direct and indirect effects on the seed yield of confectionery sunflower. 36 confectionery sunflower populations originated from different regions of Northwest Iran were characterized using 11 agromorphological traits including: Days to 50% flowering, plant height, stem diameter, head diameter, number of leaves, leaf length, leaf width, petiole length, number of seeds per head, 100-seed weight and seed yield. Phenotypic correlations results show that seed yield per plant was positively and significantly associated with 100-seed weight, head diameter, number of seeds per head, stem diameter and plant height. Path coefficient analysis revealed that number of seed per head, 100-seed weight, and head diameter has positive direct effect on seed yield. Therefore, selection based on these characters would be more effective to improving seed yield in confectionery sunflower in breeding programs.Key words: Helianthus annuus L., direct effect, phenotypic correlation, indirect selection

Collection, evaluation and classification of Iranian confectionary sunflower (Helianthus annuus L.) populations using multivaraite statistical techniques

Characterization of confectionary sunflower germplasm resources is critical to their efficient collection and management as well as for breeding programs. Thirty six (36) confectionary sunflower populations originating from different regions of Northwest Iran were characterized using 15 agro-morphological traits. Among the studied traits, high coefficients of variation were observed for harvest index (48.36), seed yield (42.07) and petiole length (41.63). Cluster analysis using Ward's method classified the 36 populations into four groups. A large number of genotypes was placed in cluster III (16 genotypes) followed by cluster I (13), cluster IV (4) and cluster II (3). Clusters I, III and VI include genotypes from different sources indicating no association between clustering pattern and eco-geographical distribution of genotypes. The maximum inter-cluster distance of 9.03 was observed between clusters II and VI indicating the possibility of high heterosis if individuals from these two clusters are cross-bred. Principal component analysis resulted in the first four components with Eigen value greater than one accounting for 78% of the total variation. The results of PCA were closely in line with those of cluster analysis. These results can now be used by breeders to develop high yielding sunflower hybrids.Key words: Cluster analysis, confectionary sunflower, genetic variability, principal component analysis

Nanostructured Modified Electrode for Electrocatalytic Determination of Epinephrine in the Presence of Acetaminophen

Abstract In this paper, a nanostructured modified electrode was fabricated by incorporating of 2,2′-[1,9-nonanediylbis(nitriloethylidyne)]-bishydroquinone (NNH) as a newly synthesized modifier and TiO 2 nanoparticles to the carbon paste (MTCPE) and then was used for the electroanalysis of epinephrine (EP). The electrochemical studies were carried out by using cyclic voltammetry, chronoamperometry and differential pulse voltammetry (DPV) techniques. It has been found that the oxidation of EP at the surface of this electrode occurs at a potential about 235 mV less positive than that of an unmodified carbon paste electrode. A dynamic range of 1.0-2000.0 µM, with a detection limit of 0.37 µM for EP, was obtained using DPV. Also, this modified electrode exhibits well separated oxidation peaks for EP and acetaminophen (AC) using DPV. JNS All rights reserve

A review on data stream classification

At this present time, the significance of data streams cannot be denied as many researchers have placed their focus on the research areas of databases, statistics, and computer science. In fact, data streams refer to some data points sequences that are found in order with the potential to be non-binding, which is generated from the process of generating information in a manner that is not stationary. As such the typical tasks of searching data have been linked to streams of data that are inclusive of clustering, classification, and repeated mining of pattern. This paper presents several data stream clustering approaches, which are based on density, besides attempting to comprehend the function of the related algorithms; both semi-supervised and active learning, along with reviews of a number of recent studies

The application of particle swarm optimization in slope stability analysis of homogeneous soil slopes

This paper applies particle swarm optimization (PSO) to find the most possible failure surface in stability analysis of homogeneous soil slopes. The stability of slopes is an important issue on geotechnical engineering. This problem includes two general concepts, factor of safety (FOS) and the critical slip surface (CSS). The resultant ratio of dividing strengthens forces by driving forces is called FOS. The critical slip surface is defined as a failure surface with the minimum value of FOS among all candidates. Regarding to the vast number of trial slip surfaces and the non-linear nature of equation of FOS, a global optimization algorithm is needed to locate CSS. As an optimization technique, the original version of PSO with little improvements in initial parameters is used. With this aim in view, we developed a computer code to find CSS by particle swarm optimization. Moreover, a sensitivity analysis is conducted to find the optimum values of initial parameters of PSO. Finally the effectiveness and efficiency of PSO code is verified and compared with the benchmark examples from the literature. The results demonstrated the ability of PSO to find CSS with better outcomes than former methods

Simulation of nitrate transport and wastewater seepage in groundwater flow system

Groundwater quantity and quality modeling is one approach for optimal use of available water resources in arid and semiarid regions. This study was conducted to simulate flow treatment and nitrate transport on Shahrekord aquifer using three-dimensional solute transport model and geographical information system. Hydraulic conductivity, specific yield and recharge values in flow simulation process and effect molecular diffusion coefficient, longitudinal dispersivity and distribution coefficient in quality model were calibrated. 120 water samples during July 2007 to June 2008 were collected monthly from 10 wells and measurements of nitrate were carried out. The results show that the developed model is successfully used to simulate flow path and nitrate transport in saturated porous media. The highest values of nitrate occur along Bahram–Abad village and the surroundings. The groundwater quality in the area represents a complex system, which is affected by different factors of pollution, such as urban wastewater and leaching of agricultural lands

Application of Bayesian Decision Networks for groundwater resources management under the conditions of high uncertainty and data scarcity

This is the author accepted manuscript. The final version is available from Springer Verlag via the DOI in this record.This paper presents management of groundwater resource using a Bayesian Decision Network (BDN). The Kordkooy region in North East of Iran has been selected as study area. The region has been sub-divided into three zones based on transmissivity (T) and electrical conductivity (EC) values. The BDN parameters: prior probabilities and Conditional Probability Tables - CPTs) have been identified for each of the three zones. Three groups of management scenarios have been developed based on the two decision variables including "Crop pattern" and "Domestic water demand" across the three zones of the study area: 1) status quo management for all three zones represent current conditions; 2) the effect of change in cropping pattern on management endpoints and 3) the effect of future increased domestic water demand on management endpoints. The outcomes arising from implementing each scenario have been predicted by use of the constructed BDN for each of the zones. Results reveal that probability of drawdown in groundwater levels of southern areas is relatively high compared with other zones. Groundwater withdrawal from northern and northwestern areas of the study area should be limited due to the groundwater quality problems associated with shallow groundwater of these two zones. The ability of the Bayesian Decision Network to take into account key uncertainties in natural resources and perform meaningful analysis in cases where there is not a vast amount of information and observed data available – and opportunities for enabling inputs for the analysis based partly on expert elicitation, emphasizes key advantages of this approach for groundwater management and addressing the groundwater related problems in a data-scarce area.This work was performed with the support of Gorgan University of Agricultural Sci. & Natural Resources research counci