NBR/phenolic interpenetrating networks (IPNs) offer a wide variety of mechanical and physical properties at moderately high temperature. This temperature stability along with oil and fuel resistance property has made IPNs appropriate candidates for various applications. In the present work, NBR compounds containing 5, 7 and 12 phr of Novolac, as a curable phenolic resin was formulated using a two-roll mill. Low and high acrylonitrile NBR; KNB 35L and Europrene N4560 were selected in the compound and the same condition of mixing was applied in the blend preparation stage. Curing test, followed by a cooling period and the stress relaxation test were carried out consecutively and automatically in a rubber process analyzer. The samples presented various relaxation times. The relaxation curves were well estimated by Maxwell model and the PRONY coefficients were determined. Furthermore, compression test was performed on the samples, so that the set or permanent deformation of each sample was measured. The results of both tests have indicated that by adding phenolic resin into the NBR matrices, the viscoelastic behavior of the compounds become more elastic, to the detriment of the viscous component. This phenomenon would be due to IPN formation in the compounds. In addition, by increasing the phenolic resin content in the compounds, the difference between maximum and minimum torque (M H-M L) value became greater, which is an indicator of higher cross-link density and IPN formation. Swelling test results confirmed more extensive cross-links in the compounds by addition of more resin into the compound.

In this article, an attempt has been made to estimate the amount of sound transmission loss in a flat oval channel by applying the approach of statistical energy analysis. Correct ESTIMATION of sound transmission loss in an air conditioning channel is of great importance due to the harmful effects of noise pollution in the environment on human health. Simulation with the statistical energy analysis method is a powerful approach to estimate sound and vibration in problems in which we deal with complex and multi-part systems; is considered. In this method, first, a system is divided into several subsystems, and then by writing a matrix equation that includes the energy exchanges between subsystems and energy loss coefficients; It is investigated from the perspective of vibration and sound ESTIMATION.On average, the model presented in this research is able to estimate the sound transmission loss in different dimensions of the air conditioning channels according to the experimental results in the accuracy range of ± 2.5 dB. Considering that it seems that the results obtained from modeling with this method are in good agreement with the experimental data; The results of this research can be used as an efficient approach to estimate noise in oval shaped channels stretched in different lengths.

This study aimed to estimate the genetic parameters of body weight traits in Markhoz goats, using B-spline random regression models. The data used in this study included 19549 records collected during 29 years (1992-2021) in Markhoz goat Breeding Research Station, located in Sanandaj, Iran. The model used to analyze data included fixed effects (year of birth, sex, type of birth and age of dam) and random effects including direct additive genetic, maternal additive genetic, permanent environmental and maternal permanent environmental assuming homogeneous and heterogeneous residual variance during the time. Akaike (BIC) and Bayesian (BIC) information criteria were used to compare the models and bspq.4.4.4.4 was selected as the best model. The direct heritability values for birth, 3-month, 6-month, 9-month and 12-month weights were estimated to be 0.14, 0.16, 0.08, 0.28 and 0.26, respectively. Genetic correlation between body weights at birth and 3-month, birth and 6-month, birth and 9-month, birth and 12-month, 3-month and 6-month, 3-month and 9-month, 3-month and 12-month, 6-months and 9-month and 9-month and 12-month were 0.22, 0.38, 0.21, 0.56, -0.26, 0.30, 0.62, 0.86 and 0.77, respectively. The highest phenotypic correlation was between the weight of 9-month and 12-month (0.82) and the lowest correlation was between birth weight and 3-month and 6-month (0.12). The results showed that the 9-month weight is a good criterion for selection in Markhoz goats.

High voltage direct current (HVDC) transmission lines can be used to transfer bulk power over long distances. Accurate ESTIMATION of fault location in these transmission lines is very essential to speed up the maintenance operations. This paper presents a new approach for intelligent fault locating in bipolar HVDC transmission lines using the pattern recognition techniques and the machine learning algorithms. In the proposed approach, using a combination of PRONY analysis (PA) and the singular value decomposition (SVD), some useful features are extracted from the post-fault voltage signals measured at one the line terminals. Then, a pre-trained generalized regression neural network (GRNN) receives the extracted features and estimates the corresponding fault location. Tests conducted on a sample bipolar system show that the proposed fault locator has accurate and appropriate performance despite changes in fault location, fault resistance, and pre-fault current. The obtained average percentage fault location errors for the positive-pole-to-ground (PG), positive-poleto-negative-pole (PN), and positive-pole-to-negative-pole-to-ground (PNG) faults in the sample system under study are 0.264%, 0.287%, and 0.225%, respectively.

Background and Aim: At present, there are various methods for performing diagnostic tests. Due to the fact that saliva is easily available compared to other body fluids, it can be collected from patients in a noninvasive way and there is no risk of cross-infection because of it, so its use has become more common. Also, the analysis of substances in saliva can be a reflection of a person's oral and systemic conditions. Despite its advantages as a diagnostic fluid, the lack of sufficient information about the methods of collecting and storing samples prevents the repeated use of saliva. In this article, it has been tried to collect the most standard methods of saliva collection, required conditions and supplies, and how to maintain, and provide them to users. Material and Methods: In this review article, data were collected by searching articles which were published between year 2000 and 2020 in domestic and foreign journals, using databases such as: PubMed, PubMed Central, Medline, EBSCO, Google Scholar and Embase with keywords: Saliva, Dry Mouth, Xerostomia, Salivary Determination and Saliva ESTIMATION. Among the relevant authorities, the articles that were cited many times and were more up-to-date, were selected. Conclusion: It seems like using saliva in modern diagnostic tests, makes the diagnosis of many diseases easier, faster and more accurate. The standard methods of saliva collection in this article can be used as a guide for laboratory-clinical researchs by researchers.

A numerical and experimental low-velocity impact behavior of sandwich plates have been presently studied with regard to the compressibility and viscoelasticity features of their cores. Face sheets were assumed to be anisotropic composites or isotropic aluminum materials and a viscoelastic behavior has been considered for core. The boundary conditions are assumed to be simply supported or rigid. Abaqus, as FEM software, and its python script programming feature, have been used to model the specimens. To model hyper-viscoelastic nonlinear behavior of the core, Ogden hyper-foam elasticity and PRONY series approach are manipulated. To solve the numerical problem, dynamic explicit solver option with sufficient solving amplitude has been used. PRONY series have been used to model the core time-dependent behavior. In conjunction with a simple indentation experiment, FEM used to formulate a novel method for finding the PRONY series coefficients. By performing some low-velocity impact experiments, the impact force and displacement of the composite sandwich plates have been investigated. The results indicate that increasing the structural damping increases the contact time and missing energy and decreases the stored energy of the system. The structures with composite face sheets have a minimum ratio of upper face sheet displacement to lower face sheet displacement in comparison to those with the isotropic face sheets. Impact behavior of isotropic face sheet specimens are more flattened than that of the composite face sheets. In addition, the specific energy stored in the sandwich plates with composite face sheets, on different supports, is greater than that stored in the aluminum face sheets.

The paper presents a Fast Fourier Transform (FFT) based Power Spectral Density (PSD) filter for denoising the PMU signal received from the smart power system network to identify the low frequency Oscillation modes (LFO). Small disturbances are introduced during normal operation of power system causes low frequency oscillations and may hinder the power system transfer capabilities of a system. The traditional signal processing method cannot extract the information from ambient signals effectively during noisy measurement. In this paper, the performance of the PRONY analysis with reduced sampling rate is analysed for the PMU data with noiseless and noise environment. It is observed that, the performance of the PRONY approach is not satisfactory under noisy measurement data.  In the present work FFT-PSD is used to denoise the noisy measurement signal and identify the nature of the decrement factor of the low frequency oscillatory modes. The accuracy of the estimated decrement factors of modes are verified with eigenvalues to validate the proposed method. The performance of proposed method is compared with signal processing method for IEEE New England power system and found effective and suitable during noisy PMU measurements.

In non-coherent Direction Of Arrival (DOA) ESTIMATION, the goal is to determine DOA based only on the magnitude of the received sensor array signal. The advantage of the non-coherent DOA ESTIMATION is its robustness against phase errors; despite phase errors present in both sensors and phase shifters, direction of arrival can be estimated. In this paper, DOA is estimated using a frequency ESTIMATION technique which can be simply implemented by discrete Fast Fourier Transform (FFT) methods. In addition, for removing the ambiguity and solving the nonlinear equations, a reference target with high power emission is used. Simulation results, in both linear and plane array cases show the efficiency and robustness of the proposed algorithm against phase errors.

In this paper optimization of frequency offset ESTIMATION technique based on channel ESTIMATION, which is desirable for frequency selective channels and hasfast convergence speed, for using in HF channel is addressed. Because of time variations coherence time in HF channel is short, which leads to a severe degradation in the performance of above technique in this channel. An optimization of said technique is proposed in which after removing coarse frequency offset ESTIMATION and knowing residual frequency offset range, incorrect ESTIMATIONs can be removed and others can be averaged to give final correct estimate. Simulation is conducted underchannel parameters with respect to MIL-STD-188-110B. the results show that proposed optimization result in improved performance of frequency offset ESTIMATION technique based on channel ESTIMATION.