One of the major tasks of medical workforce planning system is establishing a balance between physician supply and demand throughout the country. There are different methods for estimating of SPECIALIST demand, one of them is ESTIMATION of future demand based on current demand. In this study, attendance to SPECIALISTs during two weeks and/or hospitalization during one year before initiating the study had been considered as a criterion for demand ESTIMATION. Ten thousands urban families (45518 people) in 400 clusters (each containing 25 families) were studied in 17 districts. According to the results, it is predicted that there will be a physician oversupply in pediatrics, OB/GYN, and general surgery specialties until the years 2003-2004.  

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.

BACKGROUND: Waiting time is an important indicator of patient satisfaction and the quality of care. The aim of this study is to determine the waiting time in physician offices in Tehran, Iran.METHODS: This was a cross-sectional study. The target population of this study consisted of SPECIALIST and subSPECIALIST offices in Tehran. We used a census sampling method to study the population. Data of 5475 physicians was extracted from data banks, of which 43.4% were not accessible. Thus 3098 cases were included and analyzed. We conducted telephone interviews to gather data, which was subsequently analyzed using SPSS software.RESULTS: Out of the 3098 physicians interviewed, 2585 were SPECIALISTs (83.4%); the remaining were subSPECIALISTs. The mean waiting time for a patient's first visit to a SPECIALIST was 4.30 days (SD=8.10) and for subSPECIALISTs it was 7.61 days (SD=13.98).DISCUSSION: The average waiting time in our study was less than a week for SPECIALISTs and almost a week for subSPECIALISTs. The health system in Iran has not established a complete referral system and with this situation, waiting time may have adverse effects on the health of patients. Thus studying and managing waiting time in some medical specialties or regions is a priority in our country.