The Use of Chlorophyll Meter Readings for the Selection of Maize Inbred Lines under Drought Stress

The present study aimed to investigate whether chlorophyll meter readings (SPAD) can be used as criterion of singleplant selection in maize breeding. Experimentation was performed at the ultra-low density of 0.74 plants/m2 in order the potential yield per plant to be fully expressed. R-31 honeycomb experiments were conducted in three different areas in Greece (Thessaloniki, Giannitsa and Florina) using 30 inbred lines at well-watered and water-stressed conditions during the 2012 growing season. The chlorophyll meter readings had higher rates at dry conditions, except location of Giannitsa where differences were not significant. Genotypes of highest chlorophyll meter readings were consistent across areas, emphasizing on the character’s stability. A positive correlation between the chlorophyll meter readings and grain yield was strengthening over time and culminated at the physiological maturity stage. There was a clear sign that the chlorophyll meter readings has the potential to be used for the selection of stress-adaptive genotypes and may permit modern maize to be grown at wider range of environments addressing the climate change scenarios.

Impact of Fixation Time on Subjective Video Quality Metric: a New Proposal for Lossy Compression Impairment Assessment

In this paper, a new approach for quality assessment tasks in lossy compressed digital video is proposed. The research activity is based on the visual fixation data recorded by an eye tracker. The method involved both a new paradigm for subjective quality evaluation and the subsequent statistical analysis to match subjective scores provided by the observer to the data obtained from the eye tracker experiments. The study brings improvements to the state of the art, as it solves some problems highlighted in literature. The experiments prove that data obtained from an eye tracker can be used to classify videos according to the level of impairment due to compression. The paper presents the methodology, the experimental results and their interpretation. Conclusions suggest that the eye tracker can be useful in quality assessment, if data are collected and analyzed in a proper way.

Investigation of Various PWM Techniques for Shunt Active Filter

Pulse width modulation (PWM) techniques have been the subject of intensive research for different industrial and power sector applications. A large variety of methods, different in concept and performance, have been newly developed and described. This paper analyzes the comparative merits of Sinusoidal Pulse Width Modulation (SPWM) and Space Vector Pulse Width Modulation (SVPWM) techniques and the suitability of these techniques in a Shunt Active Filter (SAF). The objective is to select the scheme that offers effective utilization of DC bus voltage and also harmonic reduction at the input side. The effectiveness of the PWM techniques is tested in the SAF configuration with a non linear load. The performance of the SAF with the SPWM and (SVPWM) techniques are compared with respect to the THD in source current. The study reveals that in the context of closed loop SAF control with the SVPWM technique there is only a minor improvement in THD. The utilization of the DC bus with SVPWM is also not significant compared to that with SPWM because of the non sinusoidal modulating signal from the controller in SAF configuration.

Energy Supply, Demand and Environmental Analysis – A Case Study of Indian Energy Scenario

Increasing concerns over climate change have limited the liberal usage of available energy technology options. India faces a formidable challenge to meet its energy needs and provide adequate energy of desired quality in various forms to users in sustainable manner at reasonable costs. In this paper, work carried out with an objective to study the role of various energy technology options under different scenarios namely base line scenario, high nuclear scenario, high renewable scenario, low growth and high growth rate scenario. The study has been carried out using Model for Energy Supply Strategy Alternatives and their General Environmental Impacts (MESSAGE) model which evaluates the alternative energy supply strategies with user defined constraints on fuel availability, environmental regulations etc. The projected electricity demand, at the end of study period i.e. 2035 is 500490 MWYr. The model predicted the share of the demand by Thermal: 428170 MWYr, Hydro: 40320 MWYr, Nuclear: 14000 MWYr, Wind: 18000 MWYr in the base line scenario. Coal remains the dominant fuel for production of electricity during the study period. However, the import dependency of coal increased during the study period. In baseline scenario the cumulative carbon dioxide emissions upto 2035 are about 11,000 million tones of CO2. In the scenario of high nuclear capacity the carbon dioxide emissions reduced by 10 % when nuclear energy share increased to 9 % compared to 3 % in baseline scenario. Similarly aggressive use of renewables reduces 4 % of carbon dioxide emissions.

Evaluation of Horizontal Seismic Hazard of Naghan, Iran

This paper presents probabilistic horizontal seismic hazard assessment of Naghan, Iran. It displays the probabilistic estimate of Peak Ground Horizontal Acceleration (PGHA) for the return period of 475, 950 and 2475 years. The output of the probabilistic seismic hazard analysis is based on peak ground acceleration (PGA), which is the most common criterion in designing of buildings. A catalogue of seismic events that includes both historical and instrumental events was developed and covers the period from 840 to 2009. The seismic sources that affect the hazard in Naghan were identified within the radius of 200 km and the recurrence relationships of these sources were generated by Kijko and Sellevoll. Finally Peak Ground Horizontal Acceleration (PGHA) has been prepared to indicate the earthquake hazard of Naghan for different hazard levels by using SEISRISK III software.

Predicting Dietary Practice Behavior among Type 2 Diabetics Using the Theory of Planned Behavior and Mixed Methods Design

This study applied the Theory of Planned Behavior model in predicting dietary behavior among Type 2 diabetics in a Kenyan environment. The study was conducted for three months within the diabetic clinic at Kisii Hospital in Nyanza Province in Kenya and adopted sequential mixed methods design combing both qualitative and quantitative phases. Qualitative data was analyzed using grounded theory analysis method. Structural equation modeling using maximum likelihood was used to analyze quantitative data. The results based on the common fit indices revealed that the theory of planned behavior fitted the data acceptably well among the Type 2 diabetes and within dietary behavior {χ2 = 223.3, df = 77, p = .02, χ2/df = 2.9, n=237; TLI = .93; CFI =.91; RMSEA (90CI) = .090(.039, .146)}. This implies that the Theory of Planned Behavior holds and forms a framework for promoting dietary practice among Type 2 diabetics.

Influence of Watertable Depth on Soil Sodicity and Salinity

In order to monitor the water table depth on soil profile salinity buildup, a field study was carried out during 2006-07. Wheat (Rabi) and Sorghum (Kharif) fodder were sown in with three treatments. The results showed that watertable depth lowered from 1.15m to 2.89 m depth at the end of experiment. With lower of watertable depth, pH, ECe and SAR decreased under crops both without and with gypsum and increased in fallowing. Soil moisture depletion was directly proportional to lowering of watertable. With the application of irrigation water (58cm) pH, ECe and SAR were reduced in cropped plots, reduction was higher in gypsum applied plots than non-gypsum plots. In case of fallowing, there was increase in pH, EC, while slight reduction occurred in SAR values. However, soil salinity showed an increasing upward trend under fallowing and its value in 0-30 cm soil layer was the highest amongst the treatments.

Burst on Hurst Algorithm for Detecting Activity Patterns in Networks of Cortical Neurons

Electrophysiological signals were recorded from primary cultures of dissociated rat cortical neurons coupled to Micro-Electrode Arrays (MEAs). The neuronal discharge patterns may change under varying physiological and pathological conditions. For this reason, we developed a new burst detection method able to identify bursts with peculiar features in different experimental conditions (i.e. spontaneous activity and under the effect of specific drugs). The main feature of our algorithm (i.e. Burst On Hurst), based on the auto-similarity or fractal property of the recorded signal, is the independence from the chosen spike detection method since it works directly on the raw data.

Methods for Data Selection in Medical Databases: The Binary Logistic Regression -Relations with the Calculated Risks

The medical studies often require different methods for parameters selection, as a second step of processing, after the database-s designing and filling with information. One common task is the selection of fields that act as risk factors using wellknown methods, in order to find the most relevant risk factors and to establish a possible hierarchy between them. Different methods are available in this purpose, one of the most known being the binary logistic regression. We will present the mathematical principles of this method and a practical example of using it in the analysis of the influence of 10 different psychiatric diagnostics over 4 different types of offences (in a database made from 289 psychiatric patients involved in different types of offences). Finally, we will make some observations about the relation between the risk factors hierarchy established through binary logistic regression and the individual risks, as well as the results of Chi-squared test. We will show that the hierarchy built using the binary logistic regression doesn-t agree with the direct order of risk factors, even if it was naturally to assume this hypothesis as being always true.

Numerical Approximation to the Performance of CUSUM Charts for EMA (1) Process

These paper, we approximate the average run length (ARL) for CUSUM chart when observation are an exponential first order moving average sequence (EMA1). We used Gauss-Legendre numerical scheme for integral equations (IE) method for approximate ARL0 and ARL1, where ARL in control and out of control, respectively. We compared the results from IE method and exact solution such that the two methods perform good agreement.

Discrete Time Optimal Solution for the Connection Admission Control Problem

The Connection Admission Control (CAC) problem is formulated in this paper as a discrete time optimal control problem. The control variables account for the acceptance/ rejection of new connections and forced dropping of in-progress connections. These variables are constrained to meet suitable conditions which account for the QoS requirements (Link Availability, Blocking Probability, Dropping Probability). The performance index evaluates the total throughput. At each discrete time, the problem is solved as an integer-valued linear programming one. The proposed procedure was successfully tested against suitably simulated data.

Schmitt Trigger Based SRAM Using Finfet Technology- Shorted Gate Mode

The most widely used semiconductor memory types are the Dynamic Random Access Memory (DRAM) and Static Random Access memory (SRAM). Competition among memory manufacturers drives the need to decrease power consumption and reduce the probability of read failure. A technology that is relatively new and has not been explored is the FinFET technology. In this paper, a single cell Schmitt Trigger Based Static RAM using FinFET technology is proposed and analyzed. The accuracy of the result is validated by means of HSPICE simulations with 32nm FinFET technology and the results are then compared with 6T SRAM using the same technology.

Determining Optimal Demand Rate and Production Decisions: A Geometric Programming Approach

In this paper a nonlinear model is presented to demonstrate the relation between production and marketing departments. By introducing some functions such as pricing cost and market share loss functions it will be tried to show some aspects of market modelling which has not been regarded before. The proposed model will be a constrained signomial geometric programming model. For model solving, after variables- modifications an iterative technique based on the concept of geometric mean will be introduced to solve the resulting non-standard posynomial model which can be applied to a wide variety of models in non-standard posynomial geometric programming form. At the end a numerical analysis will be presented to accredit the validity of the mentioned model.

Development of Heterogeneous Parallel Genetic Simulated Annealing Using Multi-Niche Crowding

In this paper, a new hybrid of genetic algorithm (GA) and simulated annealing (SA), referred to as GSA, is presented. In this algorithm, SA is incorporated into GA to escape from local optima. The concept of hierarchical parallel GA is employed to parallelize GSA for the optimization of multimodal functions. In addition, multi-niche crowding is used to maintain the diversity in the population of the parallel GSA (PGSA). The performance of the proposed algorithms is evaluated against a standard set of multimodal benchmark functions. The multi-niche crowding PGSA and normal PGSA show some remarkable improvement in comparison with the conventional parallel genetic algorithm and the breeder genetic algorithm (BGA).

The Dynamics of Oil Bodies in A. thaliana Seeds: A Mathematical Model of Biogenesis and Coalescence

The subcellular organelles called oil bodies (OBs) are lipid-filled quasi-spherical droplets produced from the endoplasmic reticulum (ER) and then released into the cytoplasm during seed development. It is believed that an OB grows by coalescence with other OBs and that its stability depends on the composition of oleosins, major proteins inserted in the hemi membrane that covers OBs. In this study, we measured the OB-volume distribution from different genotypes of A. thaliana after 7, 8, 9, 10 and 11 days of seed development. In order to test the hypothesis of OBs dynamics, we developed a simple mathematical model using non-linear differential equations inspired from the theory of coagulation. The model describes the evolution of OB-volume distribution during the first steps of seed development by taking into consideration the production of OBs, the increase of triacylglycerol volume to be stored, and the growth by coalescence of OBs. Fitted parameters values show an increase in the OB production and coalescence rates in A. thaliana oleosin mutants compared to wild type.

The Supplier Relationship Management Market Trends

The paper introduces and discusses definitions and concepts from the supplier relationship management area. This review has the goal to provide readers with the basic conditions to understand the market mechanisms and the technological developments of the SRM market. Further on, the work gives a picture of the actual business environment in which the SRM vendors are in, and the main trends in the field, based on the main SRM functionalities i.e. e-Procurement, e-Sourcing and Supplier Enablement, which indicates users and software providers the future technological developments and practises that will take place in this area in the next couple of years.

Genetic Algorithm Based Optimal Control for a 6-DOF Non Redundant Stewart Manipulator

Applicability of tuning the controller gains for Stewart manipulator using genetic algorithm as an efficient search technique is investigated. Kinematics and dynamics models were introduced in detail for simulation purpose. A PD task space control scheme was used. For demonstrating technique feasibility, a Stewart manipulator numerical-model was built. A genetic algorithm was then employed to search for optimal controller gains. The controller was tested onsite a generic circular mission. The simulation results show that the technique is highly convergent with superior performance operating for different payloads.

Performance Analysis of Parallel Client-Server Model Versus Parallel Mobile Agent Model

Mobile agent has motivated the creation of a new methodology for parallel computing. We introduce a methodology for the creation of parallel applications on the network. The proposed Mobile-Agent parallel processing framework uses multiple Javamobile Agents. Each mobile agent can travel to the specified machine in the network to perform its tasks. We also introduce the concept of master agent, which is Java object capable of implementing a particular task of the target application. Master agent is dynamically assigns the task to mobile agents. We have developed and tested a prototype application: Mobile Agent Based Parallel Computing. Boosted by the inherited benefits of using Java and Mobile Agents, our proposed methodology breaks the barriers between the environments, and could potentially exploit in a parallel manner all the available computational resources on the network. This paper elaborates performance issues of a mobile agent for parallel computing.

Dynamic Modeling and Simulation of Heavy Paraffin Dehydrogenation Reactor for Selective Olefin Production in Linear Alkyl Benzene Production Plant

Modeling of a heterogeneous industrial fixed bed reactor for selective dehydrogenation of heavy paraffin with Pt-Sn- Al2O3 catalyst has been the subject of current study. By applying mass balance, momentum balance for appropriate element of reactor and using pressure drop, rate and deactivation equations, a detailed model of the reactor has been obtained. Mass balance equations have been written for five different components. In order to estimate reactor production by the passage of time, the reactor model which is a set of partial differential equations, ordinary differential equations and algebraic equations has been solved numerically. Paraffins, olefins, dienes, aromatics and hydrogen mole percent as a function of time and reactor radius have been found by numerical solution of the model. Results of model have been compared with industrial reactor data at different operation times. The comparison successfully confirms validity of proposed model.

Mechanisms of Organic Contaminants Uptake and Degradation in Plants

As a result of urbanization, the unpredictable growth of industry and transport, production of chemicals, military activities, etc. the concentration of anthropogenic toxicants spread in nature exceeds all the permissible standards. Most dangerous among these contaminants are organic compounds having great persistence, bioaccumulation, and toxicity along with our awareness of their prominent occurrence in the environment and food chain. Among natural ecological tools, plants still occupying above 40% of the world land, until recently, were considered as organisms having only a limited ecological potential, accumulating in plant biomass and partially volatilizing contaminants of different structure. However, analysis of experimental data of the last two decades revealed the essential role of plants in environment remediation due to ability to carry out intracellular degradation processes leading to partial or complete decomposition of carbon skeleton of different structure contaminants. Though, phytoremediation technologies still are in research and development, their various applications have been successfully used. The paper aims to analyze mechanisms of organic contaminants uptake and detoxification in plants, being the less studied issue in evaluation and exploration of plants potential for environment remediation.