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Objective: Lymnaea palustris was previously found in Mazandaran province but there was not any report about its parasitologic aspects. This study was conducted to finding ecological and Parasitological aspects of snail in Mazandaran province, North of Iran. Materials and Methods: In this descriptive study, more than 181 locations, were checked, in 36 locations, colonies of the snail were found and 490 snails were collected. After diagnosis of snails as Lymanea palustris, in laboratory, they were crushed and their probable cercaria was checked out by a dissecting microscope. Data were analyzed and processed by ArcGIS 9.2 and Microsoft Office 2003 for descriptive analysis. Results: from 490 snails, 6 cases (1.22%) were infected with trematode larval stage. These cercariae were classified as echinostomaercaria. Optimum temperature for the snails was 15-19 degrees of celsius and optimum dissolved salt (TDS) was 200-400 ppm. Population of colonies were raised in autumn and winter but infected snails were seen in summer. Conclusion: This study could show the ecological pattern, distribution, and population dynamic of the snail. Also the existence of echinostomaercaria which is cercaria, generally belong to the Echinostoma sp, indicates veterinary and parasitological importance of local snails. It is probable these parasite, infect man also. More studies on definitive host and exact species of parasite are proposed.

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In this paper, a quantum intelligent robust controller via a combination of sliding mode control with boundary layer and quantum neural networks, for uncertain nonlinear systems in presence of external disturbances, is presented. Based on the adjustable time variant rejection regulator and rejection parameter, a time variant sliding surface as an adaptive chain of the first ordered low pass filters is defined. A three layers quantum neural network is designed to identify the uncertain nonlinear functions in system dynamics. In this method, the control gain and the break-frequency bandwidth are tuned adaptively. Also, the effects of uncertainties and the un-modeled frequencies are eliminated and chattering phenomenon doesn’t occur. Also, for facilitating analytical theory of the presented method and derivation of the adaptive laws a theorem is proved. Finally, the simulated examples show that the proposed method presents an intelligent adaptive robust tracking control such that the control amplitudes and the integral absolute error index of the tracking trajectory are much less than the other methods. Therefore, effective identification, eliminating the effects of system uncertainties, adjustable control gain and break-frequency bandwidth and more accurate tracking are some of the advantages of this method.
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In this paper, we investigate chaos in attitude dynamics of a rigid satellite in an elliptic orbit analytically and numerically. The goal in the analytical part is to prove the existence of chaos and then to find a relation for the width of chaotic layers based on the parameters of the system. The numerical part is aimed at validating the analytical method using the Poincare maps and the plots obtained on the sensitivity to initial conditions. For this end, first, the Hamiltonian for the unperturbed system is derived. This Hamiltonian has three degrees of freedom due to the three-axis free rotation of the satellite. However, the unperturbed attitude dynamics has two first-integrals of motion, namely, the energy and the angular momentum. Next, we use the Serret-Andoyer transformation and reduce the unperturbed system Hamiltonian to one-degree of freedom. Then, the gravity gradient perturbation due to moving in an elliptic orbit is approximated in Serret-Andoyer variables and time. Due to this approximation and simplification, the system Hamiltonian transforms to a one-degree-of-freedom non-autonomous one. After that, Melnikov’s method is used to prove the existence of chaos around the heteroclinic orbits of the system. Finally, a relation for calculating the width of chaotic layers around the heteroclinic orbits in the Poincare map of the Serret-Andoyer variables is analytically derived. Results show that the analytical method gives a good approximation of the width of chaotic layers. Moreover, the results show that the analytical method is accurate even for orbits with large eccentricities.

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In this paper, a new hybrid intelligent method is presented for detecting the bearing faults in the various rotating speeds. The vibration signals are collected in four conditions, including the normal state, the faulty inner race, the faulty outer race, and the faulty bearing element. Firstly, twenty-two statistical features in the time domain and four frequency features, three Wavelet packet decomposition (WPD), and the first five intrinsic mode functions obtained by the empirical mode decomposition (EMD) are extracted from the original signal; finally, the feature vector for each signal sample has 424 features. However, in the high dimensional feature matrix, there may exist the insensitive features to the presence of defects. Therefore, in this study, the compensation distance evaluation technique (CDET) is used to select the optimal features. Then, the selected features are used as the inputs of the support vector machine (SVM) classifier to diagnose the bearing conditions. In the CDET method, there is a threshold indicator that plays a decisive role in choosing the desired attributes. Also, the SVM method has some parameters that need to be set during the fault detection process. Therefore, the particle swarm optimization (PSO) algorithm is used to determine the optimal threshold in the CDET method and the optimal SVM parameters, so that the prediction error of the bearing conditions and the number of the selected features are minimized. The obtained results demonstrate that the selected features are well able to differentiate between different bearing conditions at various speeds. Comparing the results of this paper with other fault detection methods indicates the ability of the proposed method.

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The main purpose of this study is to present a model of the planning, recruitment, select and redundancy of human resource and its adaptation to the organizations of the civil service management act audience. The research method is exploratory mixed research projects. The statistical population of the first phase (qualitative) included the faculty of public administration with human resources orientation and the statistical population of the second phase (quantitative) of managers and human resource specialists of public institutions. In the first phase (qualitative) of the research, the data were collected by semi-structured interview and in the second phase (quantitative), semi-open questionnaires and 97 questions were distributed. In the first phase, the data were coded by Atlasti software, and in the second phase, the model test was derived from the first phase of the study by structural equation modeling using PLS software and descriptive statistics, central indices and consensus percentage on the model and results indicate that %89 of the participants had a consensus on the conceptual model of the research, and all dimensions of the model were explained. The main issue of the present research is planning for human resource development in the organization, which has been formulated based on the causal, ground and interventional conditions, its dimensions and strategies for its realization, and then the final model was presented based on it.