Background: The lack of couples’ intimacy is one of the main concerns of experts in the field of psychology and counseling. It is one of the most important causes of divorce. The 9th principle of International conference on population and development (ICPD) highlights the support of the family as the main unit of the society. Objectives: The study aimed to determine the socio-demographic Predictors of marital intimacy in couples. Methods: This was a cross-sectional study conducted on 118 couples referring to healthcare settings. A random sampling method was used to recruit the couples. Data were collected using the socio-demographic questionnaire, the Bagarozzi’ s marital intimacy needs questionnaire, Barton’ s communication skills questionnaire, the Hazan and Shaver’ s adult attachment styles (1678) questionnaire, and the interpersonal conflict management style (ICMSI). The collected data were analyzed using inferential and descriptive statistics. Results: A statistically significant positive correlation was found in the mean of marital intimacy between men and women. The Predictors of marital intimacy in men were the attachment style and communication skills. The Predictors of marital intimacy in women were marital satisfaction, communication skills, and conflict resolution styles. Conclusions: Future interventions to improve marital intimacy in couples should consider the following factors: marital satisfaction, marital conflicts, duration of the marriage, communication skills, conflict resolution styles, and the attachment style. It is noted that counselors should attempt to provide appropriate care for couples with the consideration of the above-mentioned factors influencing their interactions and behaviors.

Despite recent development in producing chemical medicines, associated side effects have led to increased use of medicinal plants and natural compounds. Soil salinity, especially in arid and semi-arid regions, is a serious threat to global agriculture. Nowadays, efforts have been made to find benchmarks that can effectively select salt-tolerant or salt-resistant genotypes. In this regard, the use of computer software to Predict the indices can help us for screening the most tolerant ecotypes. The objectives of the present study were to determine the best indicators of salinity tolerance using intelligent and regression models for eighteen commercial ecotypes of mint. The seedlings were planted in plastic pots and arranged in a split factorial experiment in a randomized complete block design with four replicates. The treatments consisted of four levels of salinity (0, 2. 5, 5 and 7. 5 dS m-1), two levels of harvesting time, and 18 ecotypes. The plants were grown until the flowering stage and then harvested. There was a significant difference between ecotypes in terms of calculated indices at all three levels of salinity. Indicators such as TOL, MP, GMP, YSI, STI and HM showed a significant positive correlation with YS and YP at all three levels of salinity. The cluster analysis divided the ecotypes into three distinct groups based on the calculated indices at all levels of salinity. The principal component analysis revealed that the YP, YS, TOL, MP, GMP, YSI, STI and HM were more suitable among others salt stress indices. The sensitivity analysis at 2. 5 dS m-1 salinity level showed that the HM, STI, YSI, YI, SSI and MP indices were of higher importance than the others. At 5 dS m-1 salinity level, the HM, STI, YSI, YI, GMP and MP indices showed the highest importance whereas at 7. 5 dS m-1 salinity level, the STI, YSI, YI, GMP and YP indices indicated the highest importance. In general, the results suggest that ANN(MLP) model (R2 = 0. 999) is the best model to Predict at all salinity levels. E13, E14, E15, E16 and E18 ecotypes are the most salt tolerant ecotypes which can be used for the future breeding program.

One of the geotechnical hazards in the tunnels under high overburden and high in situ stresses is the phenomenon of rock burst. Rock burst is a typical geologic phenomenon caused by excavation in rock masses. In this phenomenon, because of stress released and explosion in rock masses, they are broken as large and small pieces and are distributed, so that leads to damage of peoples or equipments. Therefore, familiar with this phenomenon and its mechanism of occurrence, is need to analyze this issue. The second part of water supply Karaj-Tehran tunnel with a length of 14 km and about 4.5 m diameter is located in Tehran province. Rock burst analysis has been carried out in the tunnel from kilometer 6 to 9.5 that is critical section because of high overburden (up to 800 m) and presence of faults and crushed zones. In this paper, for Predicting rock burst in the critical section of second part of Karaj-Tehran tunnel, four criteria including, Strain energy, Rock brittleness, Seismic energy and Tangential stress criterion are used. Analysis results show that units with high overburden have high possibility of rock burst.

This study presents the Predicted amount of precipitation, temperature and the climate simulation periods 2099-2070, 2049-2020 and 2008-1979 observation period under A2 and B2 SRES scenarios using the statistical downscaling model (SDSM) in Tehran, Zanjan, Qazvin and Rasht stations on the southern side and Ramsar, Babol and Gorgan in Northern side of the Alborz. Also, future climate was determined using the Domarten method. The main objective was to compare the climate change on two fronts in the north and south of the Alborz. The performance of model to Predict the climatic parameters was evaluated based on the coefficient of determination (R2 ) and root mean squared estimation error (RMSE). The results of Predicting the climate parameters indicate that the model simulated these parameters adequately. The results of the precipitation in all stations in period 2020-2049 compared with the period 1979-2008 show an increasing trend in all stations and the period 2070-2099 compared to observation periods show an increasing trend in precipitation; while it has a decreasing trend compared to the periods 2020-2049. In 2070-2099 and 2020– 2049 periods, the average, minimum and maximum temperature was increased relative to the observation period 1979-2008. The results of the climate determination by the Domarten method show that the climate in the Babolsar, Qazvin, Ramsar and Rasht stations will be change comparing with the observed climate in 1979-2008 in the future periods. In the Gorgan station at period 2070-2099 under the A2 scenario, the climate will change from semi-arid to the arid climate. In the Zanjan station at period 2020-2049 under the A2 scenario, the climate will change from semi-arid to Mediterranean climate and at period 2070-2099 climate from Mediterranean to semi-arid climate. This data can be simulated with high accuracy to better foresight the climatic conditions in future periods to help the future macro-management in providing better productivity of resources, particularly the water resources management.

Introduction: Pelvic relaxation and cystocele is a common problem in middle to old age women. Transabdominal ultrasound (TAS) is a noninvasive, available routine procedure in many situations. We evaluated whether TAS can Predict pelvic relaxation or not.Materials and Methods: In a cross sectional case- control study one hundred women 30 years or older were enrolled into the study. An expert female urologist examined the cases for the presence of signs and the grading of pelvic relaxation. A single radiologist blinded to pelvic exam results performed TAS. In the full bladder state the following criteria were recorded: 1. Bladder outlet funneling at rest and valsalva 2. Bladder base position in relation to the superior edge of the pubis symphysis 3. Bladder wall thickness 4. Pelvicaliceal system stasis 5.Post voiding residual urine (PVR).Results: Bladder outlet funneling can Predict pelvic relaxation (Se, 91.3%), both at rest and after valsalva. If the bladder base descent is seen below the superior edge of the pubis with the cut off point of 5 mm,it can Predict pelvic relaxation.Conclusion: TAS can be used as a safe and available modality to Predict pelvic relaxation.

In this paper, it is shown that in many cases, science can Predict the future. Based on the available information of the real system, the scientific method for future Prediction is to develop a virtual model with similar response to the real system. The classical models are usually presented with a set of linear / nonlinear, ordinary / partial differential equations. The necessary and sufficient condition for future Prediction is given by three axioms; A model with accurate description of the real system, perfect knowledge of the initial conditions, and perfect knowledge of present and future values of inputs to the system. In reality, none of these conditions are perfectly realizable and each axiom has some uncertainties. The failure in future Prediction is exactly due to these uncertainties. The model description as the major axiom is always accompanied with uncertainty and although, there is no way to vanish it, there are different methods to reduce it. Soft computing is one of the recent approaches in the past few decades, not only used for modeling of systems in the field of engineering systems, but also used in the field of human sciences such as economy, management and social sciences.

Background: The aim of this study was to investigate vertebral geometry changes and determine cutoff value of vertebral height to Predict fractures.Methods: In a cross-sectional study, 280 postmenopausal women recruited In all subjects bone mineral density and radiography of the lumbar spine performed. Lateral radiographs were evaluated for identification of vertebral fractures, using a validated semiquantitative method. T-score of vertebral height was calculated based on data extracted from Iranian Multicenter Osteoporosis Study. ROC curve used to determine cut off value of vertebral height T-score to Predict fractures. Results: The mean of age and BMI were 55.34±8.7 years and 27.73±5 kg/m2, respectively. Among osteoporotic women, 59.8% had one or more vertebral fractures and 23.8% had at least 2 fractures. In fracture group the T-score of spine and femur BMD was lower than the others. The mean of vertebral height in women without fractures was 12.94±0.6 cm, and in the patient with 4 or more fractures was 12.3, thus every fracture accompany with 1.2% decreases in the height of vertebrae.The prevalence of vertebral fracture in osteoporotic patients was 71.4% and in healthy cases 39.5%. Better estimation of vertebral height T score in ROC curve was less than -0.7.The sensitivity and specificity of the cut off value were 81.3% and 52.9%, respectively.Conclusion: Vertebral fractures are common fractures in postmenopausal women. There was a correlation between vertebral height and fractures. Vertebral geometric parameters especially height T score can be used for fracture screening.

The importance of Predicting the economic variables for policy makers and program planners is no secret to anyone. Therefore, over recent decades, several competing models have been developed. In this study, the amount of corn import to Iran is Predicted for the period 2010-2014 by using econometric techniques and artificial neural networks methods. The results show that the feed forward neural network with fewer errors and better performance compared with econometric techniques ARIMA and exponential smoothing to Predict the amount of corn imports. The study results also show that the amount of corn imports would grow in 2011 by 8 percent less than that of the previous year. Also the highest reduction in corn imports compared with that of the previous year by the amount of 11 percent decrease is related to the year 2012. So, it is necessary to increase domestic production to meet domestic needs.

One of the challenges in interpreting the results obtained in qPCR is to make sure the amplicons are specific and that the melting curve analysis is used to examine it. Additional peaks in the melting curve is not always indicative of a problem, for this purpose, in this paper, a webbased tool called uMelt SM is suggested to researchers as a practical and simple way for the correct analysis of the melting curve which provides the possibility of Predicting the DNA melting curve and denaturation profiles of the high-fluorescence resolution of PCR products. The results of this study showed that the melting curves were generated based on parameters were generated and an appropriate algorithm for working with this software was presented. Finally, actin and superoxide dismutase genes from Pyricularia oryzae were presented as a suitable model for determining the Predicted curve using this software and Real-Time PCR curve was also drawn. Results of the uMelt SM Predicted melting curves showed a high degree of compliance with the real-time PCR melting curves, which confirms the advantages of ease of use, saving time, cost, and effort in the experimentalist part when using uMelt SM software.