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.

Objective: To analyze and compare four methods for estimating the chance of treatment success in infertile couples. Materials and methods: In a retrospective cohort study, information on demographic and clinical features, including age, body mass index (BMI), duration of infertility, semen analysis, previous history of treatment and clinical examination of infertile couples were analyzed. Treatment success (childbearing) was calculated with four methods as live birth ratio, conditional probability and survival analysis (life table and Kaplan-Meyer method) and results are compared. Results: The fertility ratio for the first treatment cycle was 29. 72% which decreased to 23. 13% by total treatment cycles. The success rate was 75. 4%. With conditional probability calculation at the end of the five treatment cycles. With the life table method in a five-year period, the probability for live birth was 78% and by Kaplan-Meyer method 73. 1% and the median of treatment time was 562 days. Conclusion: Calculation of infertility treatment success rate by only simple live birth ratio of childbearing couples is associated with underestimation. Using the conditional probability method reduces that underestimation, but it is not considered the censored cases in the treatments. It seems life table (as a proxy of survival analysis) presents the closest estimation to clinical facts with considering the repetition of the treatment cycle and the duration of treatment.

One of the major issues that investors are facing with in capital markets is decision making about selecting an appropriate stock exchange for investment and selecting an optimal portfolio. This process is done through the risk and expected return assessment. On the other hand, in portfolio selection problems if the assets' expected returns are normally distributed, variance and standard deviation are used as a risk measure. However, the expected returns on assets are not necessarily normal and sometimes have significant differences from normal distribution. This paper offers an optimal portfolio by introducing conditional value at risk (CVaR) as a measure of risk in a nonparametric framework considering a given expected return. This method is compared with the linear programming method.The data used in this study consists of monthly returns of 15 companies selected from the top 50 companies in Tehran Stock Exchange during the winter of 1392 which is considered from April of 1388 to June of 1393.The results of this study show the superiority of the nonparametric method over the linear programming method while the nonparametric method is much faster than the linear programming method.

In this paper, we study the global truncation error of the linear multistep methods (LMM) in terms of local truncation error of the corresponding Runge-Kutta schemes. The key idea is the representation of LMM with a corresponding Runge-Kutta method. For this, we need to consider the multiple step of a linear multistep method as a single step in the corresponding Runge-Kutta method. Therefore, the global error estimation of a LMM through the Runge-Kutta method will be provided. In this estimation, we do not take into account the effects of roundoff errors. The numerical illustrations show the accuracy and efficiency of the given estimation.

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.

Longitudinal studies are very common in medical, behavioral, and interventional sciences. One measure of effect of interest in longitudinal studies is risk ratio, naturally estimated by log-binomial regression which suffers from convergence problems. Odds ratio (OR) does not approximate risk ratio (RR) well when the outcome is common, so alternative methods have been introduced in cohort studies with one follow-up visit. In this paper, we illustrate two simple methods: the COPY method and the modified log-Poisson regression for RR estimation in longitudinal data setting. Our unpublished simulation study on RR estimation in longitudinal data setting suggests that the COPY method performs well in terms of closeness of the RR estimate and true RR (mean square error) and so we suggest this method for RR estimation in longitudinal data setting.

Kernel method is one of the most common nonparametric density estimation and recently B-spline is used for estimation of a probability density function. These two methods in some how depend on selecting a smoothing parameter that has an important effect on precision of the estimators. In this paper, we consider kernel and B-spline methods of density estimation and smoothing parameter selection for these two methods. Then, the accuracy of the obtained estimators is compared by their mean square errors. Also, the effect of the number and dispersion of data on precision of estimators are studied. The results show that for a symmetric probability density, if the dispersion of data increases, the precision of both estimators decreases, while, for an asymmetric probability density function, the precision of the estimators increases for dispersion data.

Potential Evapotranspiration (PET) is one of the important elements in hydrologic cycle which is required to be estimated in many fields such as irrigation, drainage and hydrological studies. This element represents potential losses from moist soil layer and vegetation cover. In this research different methods (Blaney-Criddle, Thorenthwaite, Penman and Hargreaves- Samani) are applied and then their results were compared with Fao Penman-Montieth method (as reference) and the best one is selected and suggested to estimate PET in Mazandaran province. The results show that the Blaney-Criddle has the lowest standard error and the highest correlation with the Fao Penman-Montieth method in the province. The results also show that the Blaney-Criddle method estimated PET about 5% lower than the reference method. Furthermore the results indicate that PET decreases from east to west of the province.

Nanoparticles are materials which have at least one of their dimensions (length, width, height) at the nano scale (among 1 and 100 nm). Nanofluids are obtained from the distribution of particles with nano dimensions in normal fluids. Common fluids such as water, oils and ethylene glycol, which are usually used in heat transfer, have limited ability in terms of thermal properties. The interesting properties of nanofluids (such as high heat transfer coefficient) and the great potential they show for increasing heat transfer have caused this group of fluids to be in the focus of researchers' attention in recent years. One of the key factors in optimizing the properties of these fluids is their stability. The gathering of particles and their agglomeration increases the possibility of sedimentation, reduces the stability of the suspension, and causes the loss of the properties of the suspension, such as thermal conductivity, viscosity, and increase in heat capacity. In this research, methods of increasing stability and inspection tools were investigated. The results showed that the simultaneous use of ultrasonic vibration and surface activating substances (surfactant) has a significant effect on the stability of nanofluid. And two methods of using DLS light scattering and ultraviolet-visible absorption spectrometry have been used by many researchers in their research in order to check stability.