Background: Increased environmental protection concerns urge more effort to develop new catalysts for the abetment of greenhouse gases. N2O is known as a powerful greenhouse gas. The literature review revealed that various catalysts have been developed for the direct decomposition of N2O. Special attention was given to the cobalt-based spinel oxides. However, there is a lack of information about the performance of the cadmium promoted spinels for N2O abetment. Objective: This paper addresses the nitrous oxide direct decomposition over a novel series of Cd- Co catalysts. Method: These catalysts, with Cd/(Cd + Co) ratios 0.00-0.333, were prepared with the aid of the co-precipitation route, which is followed by calcination at 500 °C. Characterization of these catalysts was performed employing TGA-DTA, XRD, FTIR, N2 adsorption/desorption, and atomic absorption spectrophotometry. Results: Phase analysis revealed the absence of a solid-state interaction between CdO and Co3O4. However, it was found that increasing the Cd/(Cd + Co) ratio is associated with continuous enhancement of the N2O decomposition activity. The activity was correlated with the presence of catalyst’s redox couples. Moreover, the role of the Cd presence in improving the activity was discussed. Finally, the activity performance change accompanying the calcination temperature raise was also investigated. Conclusions: Presence of cadmium has a positive effect on the N2O decomposition performance of Co3O4. Activity increased continuously with Cd/(Cd + Co) ratio increase over the examined range 0.083–0.333 structural, textural, and electronic roles of cadmium were proposed.

In this paper, a series of zinc cobaltite catalysts with the general formula Znx-Co1-xCo2O4 (x = 0.25, 0.50, 0.75 and 1.0) has been prepared using the co-precipitation method. Thermal analyzes (TGA and DTA) were used to follow up the thermal events accompanying the heat treatment of the parent mixture. Based on these results, the various parent mixtures were calcined at 500℃. The obtained solid catalysts were characterized by using XRD, FT-IR and N2-adsorption. The catalytic decomposition of N2O to N2 and O2 was carried out on the zinc-cobaltite catalysts. It was found that partial replacement of Co2+ by Zn2+ in Co3O4 spinel oxide led to a significant improvement in their N2O decomposition activity. Moreover, the catalytic activity was found to be depended on the calcination temperature utilized.

In this investigation, the direct catalytic decomposition of N2O into N-2 and O-2 was performed over CuxCo1-xCo2O4 (x = 0.0 <= x <= 1.0) spinel-oxide catalysts. These catalysts were synthesized by the co-precipitation method followed by calcination at 500 degrees C. The activity results demonstrated that the partial replacement of Co2+ by Cu2+ in the spinel-oxide Co3O4 led to a significant improvement in the N2O decomposition. Additionally, the activity was found to be controlled by other parameters, including the size of the spinel crystallites, the surface area of the catalysts, and the presence of residual potassium ions. (C) 2014 The Korean Society of Industrial and Engineering Chemistry. Published by Elsevier B.V. All rights reserved.

The status of tomato leaf-miner, Tuta absoluta (Meyrick), at Matrouh Governorate, Egypt was investigated under the greenhouse conditions during 2010 season as the first documented data concerting the crossing of this pest into the Egyptian borders coming from Libya. In both El-Kasr region and Siwa Oasis, the periodical monitoring of T absoluta male moths on both tomato and eggplant were carried out using the sex pheromone lure baited traps. Also, the influence of male collection technique and one tracer spraying on declining the larval infestation were evaluated. Data declared that, tomato was the most preferable host for T absoluta than other solanaceous crops, the in-time hanging of sex pheromone baited traps inside the tomato or eggplant greenhouse besides tracer sprayirig when necessary were the factors that ensured the achievement of less larval infestation. In addition, the influence of neighbor solanaceous crops on the infestation outbreak was also considered. Also, the detection of T absoluta larvae on the wild solanaceous shrub, Solanum nigrum (Black nightshade) was documented for the first time within the valleys of Matrouh Governorate. Mass trapping and lure and kill application of pheromone have been found to be effective for controlling T absoluta.

Factors affecting the use of cheap and ecofriendly pretreated bagasse for potential removal of methylene blue (basic dye) and orange II (acid dye) from wastewater were studied. Sugarcane bagasse was pretreated with propionic acid with the aim to effectively adsorb the above mentioned two dyes at varying dye concentrations, adsorbent dosage, pH and contact time. The kinetics of dye sorption processes fit a pseudo-second-order for methylene blue and pseudo-first-order for orange II kinetic models. Adsorption isotherms fit well into the Langmiur equation, where the maximum sorption capacities are 59. 9 and 26.7 mg/g for methylene blue and orange II, respectively.

This paper presents a novel algorithm for recognizing and classifying the power quality events based on Park's transformation, where the three rotating abc phases are transferred to three equivalent stationary dq0 phases d-q reference frame. This transformation is implemented, either for three-phase or single phase circuits. The proposed algorithm transferred the utility signal to a complex phasor transformation from time domain to frequency domain. The magnitude of this phasor depends on the magnitude of the signal either a three-phase or a single phase signal. The proposed technique produces the complex phasor loci that depend on the type of power quality event; voltage sags, voltage flickers, voltage swell, and harmonics. The time of starting the disturbance is chosen randomly and the length of disturbance is arbitrary. Implementation of this technique is succeeded in recognizing and classifying the power quality events. Simulated results are presented within the text, for three-phase and single phase events.

In this paper, nitrous oxide decomposition over a series of MCO3–Co3O4 (M = Ca, Sr, Ba) catalysts having M/Co ratios of 0.1–0.4 has been studied. The various catalysts were characterized using thermal (TGA, DTA), XRD, IR and N2 sorption techniques. N2O decomposition activity was found to be dependent on the type of the alkaline earth cation, the M/Co ratio, cobalt oxide crystallites sizes, and the calcination temperature.

In this paper, the preparation and characterization of crystalline terbium oxide via thermal decomposition of acetate precursor is reported. The decomposition pathway of the parent salt was followed using TGA, DTA, and in situ electrical conductivity in air and nitrogen atmospheres. The obtained results indicated that, thermal decomposition of terbium acetate proceeded with the loss of water molecules, in two steps, below 150°C followed by decomposition in the temperature range of 300–550°C, throughout different intermediates, to give Tb4O7 as a final product. The calcination products, obtained by heating the parent salt for 3h in air at various temperatures, were characterized using IR, XRD, SEM, nitrogen adsorption, and electrical conductivity measurements. It was demonstrated that Tb4O7 represents the major phase for the samples calcined at 600–900°C. The role of Tb3+–Tb4+ redox couple in enhancing the electrical conductivity of the calcination products was also discussed.

We present, in this paper, an approach for identifying the frequency and amplitude of voltage flicker signal that imposed on the nominal voltage signal, as well as the amplitude and frequency of the nominal signal itself. The proposed algorithm performs the estimation in two steps; in the first step the original voltage signal is shifted forward and backward by an integer number of sample, one sample in this paper. The new generated signals from such a shift together with the original one is used to estimate the amplitude of the original signal voltage that composed of the nominal voltage and flicker voltage. The average of this amplitude gives the amplitude of the nominal voltage; this amplitude is subtracted from the original identified signal amplitude to obtain the samples of the flicker voltage. In the second step, the argument of the signal is calculated by simply dividing the magnitude of signal sample with the estimated amplitude in the first step. Calculating the arccosine of the argument, the frequency of the nominal signal as well as the phase angle can be computing using the least error square estimation algorithm. Simulation examples are given within the text to show the features of the proposed approach.

This paper introduces new applications to Simulated Annealing (SA) optimization algorithm for measuring the voltage flicker magnitude and frequency as well as the harmonics contents of the voltage signal, for power quality analysis Moreover, the power system voltage magnitude, frequency and phase angle of the fundamental component is estimated by the proposed technique. This is a nonlinear optimization problem in continuous variables. An efficient SA algorithm with an adaptive cooling schedule and a new method for variable discretization are implemented. The new algorithm minimizes the sum of the absolute value of the error in the estimated voltage signal, and does need any approximation in modeling the voltage signal. The proposed algorithm is tested on simulated and actual recorded data. Effects of sampling frequency as well as the number of samples on the estimated parameters are discussed, ft is shown that the proposed algorithm is able to identify the parameters of the voltage signal.

Thermal events encountered throughout the heat treatment of praseodymium acetate, Pr(CH3COO)3·H2O, were studied in nitrogen and air atmospheres. The samples calcined at the 300–700°C temperature range were characterized using XRD, IR and N2 adsorption. Moreover, in situ electrical conductivity was employed to follow up the formation of the different decomposition intermediates. The results indicated that the anhydrous salt decomposes to the final product, PrO1.833, through the formation of the following intermediates: Pr(OH)(CH3COO)2, PrO(CH3COO) and Pr2O2(CO3). PrO1.833 formed at 500, 600, and 700°C possesses a surface area of 17, 16 and 10m2/g and crystallites size of 14, 17 and 30nm, respectively.

This paper presents a novel and reliable technique for estimation of a distorted signal frequency. Unlike the other available techniques, the proposed algorithm does not need linearization to the signal voltage and or current. The proposed technique uses the samples available for the voltage and or current signal in the relay location to estimate the signal fundamental frequency. The frequency of the signal is calculated from the arccosine of two successive samples for a pure sinusoidal. The least errors square algorithm is used to minimize the signal errors, noise and harmonics. The frequency is estimated from a closed formula that easily can be programmed on the microprocessor based frequency estimation. Different simulated examples are offered within the text and different critical parameters that affect the performance of the proposed algorithm are discussed.

This paper presents a novel technique for tracking voltage flicker occurring in electric power systems. Voltage flicker tracking is essential for electric power quality analysis. The instantaneous voltage flicker magnitude, frequency and phase are estimated using Kalman filtering technique. This approach is based on expressing voltage flicker as a discrete time linear dynamic system model using flicker parameters as the system parameters. An extended state space model is adapted for the Kalman filter to estimate the parameters. Fuzzy rule-based logic is used to tune-up the system-noise and measurement-noise levels by adjusting their covariance matrices using flicker measurements.

We compared in a prospective fashion the 2-years outcome of rotoresection to transurethral resection of the prostate.

A linear time-varying fuzzy load model for solving the short-term electric load forecasting problem is presented. The model utilises a moving window of current values of weather data as well as the recent past history of load and weather data. The parameters of this model are assumed to be fuzzy numbers with a triangular membership function yielding a fuzzy load that has both central and spread values. Both the load and load error are predicted for the following 24hours on an hourly basis. The forecasting method is based on state space and the Kalman filtering prediction approach in conjunction with fuzzy rule-based logic. The technique is used recursively to estimate the optimal load forecast fuzzy parameters for each hour of the day. The central values of the fuzzy parameters represent the crisp forecast values while the spread values represent the amount of variation of the forecast. The predicted load spread value provides an approximate envelope of the extremes the load possibly takes. The effectiveness of the approach is demonstrated on real load and weather data which show the load forecast with a mean absolute percent error of less than 0.7% and absolute percent error standard deviation of 0.9%.

This paper presents a new technique for one-year long-term electric power load forecasting problem. The technique is suitable to forecast daily load profiles with a lead-time from several weeks to a few years. The proposed algorithm is mainly based on multiple simple linear regression models used to capture the shape of the load over a certain period of time (one year), in a two-dimensional layout (24 hours x 52 weeks). The regression models are then recursively used to project the 2D load shape for the next period of time (next year). Load demand annual growth is estimated and incorporated in Kalman filtering algorithm to improve the load forecast accuracy obtained, so far, from the regression models. The results show a one-year load prediction with mean average percentage error less than 2.3% of the actual demand load and a standard deviation of 4.6 MW. The algorithm using historic data for different electric utilities may produce different accuracies. But, in general, for long-term load forecasting, an error level up to 10% is acceptable.