Prevalence of Posttraumatic Stress Disorder Following the Earthquake in Iran and Pakistan: A Systematic Review and Meta-Analysis.

Posttraumatic stress disorder (PTSD) is a common mental disorder following traumatic events. The present study was conducted to understand the prevalence of PTSD after the earthquake in Iran and Pakistan. The review includes all articles published from inception to March 2019. The pooled prevalence for overall PTSD was 55.6% (95% CI: 49.9-61.3). It was 60.2% (95% CI: 54.1-66.3) and 49.2% (95% CI: 39.4-59) for Iranian and Pakistani survivors, respectively. Women experienced higher incidence of PTSD than men. The variation of PTSD based on the clinical interview was lower than the self-report approach. The interval time between the earthquakes and the assessment showed that the prevalence of PTSD decreased over time. The prevalence of PTSD in Iran and Pakistan was higher than the global average, and the rate of the disorder in Iran was higher than in Pakistan. Sex, method of assessment, and time lag between the occurrence of disaster and assessment of PTSD affect the prevalence.

Artificial Neural Network to Forecast Enhanced Oil Recovery Using Hydrolyzed Polyacrylamide in Sandstone and Carbonate Reservoirs.

Polymer flooding is an important enhanced oil recovery (EOR) method with high performance which is acceptable and applicable on a field scale but should first be evaluated through lab-scale experiments or simulation tools. Artificial intelligence techniques are strong simulation tools which can be used to evaluate the performance of polymer flooding operation. In this study, the main parameters of polymer flooding were selected as input parameters of models and collected from the literature, including: polymer concentration, salt concentration, rock type, initial oil saturation, porosity, permeability, pore volume flooding, temperature, API gravity, molecular weight of the polymer, and salinity. After that, multilayer perceptron (MLP), radial basis function, and fuzzy neural networks such as the adaptive neuro-fuzzy inference system were adopted to estimate the output EOR performance. The MLP neural network had a very high ability for prediction, with statistical parameters of R2 = 0.9990 and RMSE = 0.0002. Therefore, the proposed model can significantly help engineers to select the proper EOR methods and API gravity, salinity, permeability, porosity, and salt concentration have the greatest impact on the polymer flooding performance.

Identifying the effective factors on the transition to the third-generation university: A qualitative study.

BACKGROUND: Iranian universities optimistically can be regarded as second-generation research-centered universities which train people who can only fill the predefined occupational gaps. These universities are doing very little to become third-generation universities. It seems that medical science universities have a huge capacity to create and expand entrepreneurship in health care because of their diverse activities in health services. The present study aimed to investigate the effective factors affecting the Iranian medical universities transition to third-generation universities. METHODS: The present study is a qualitative study which was carried out in Kerman University of Medical Sciences. The study population was the faculty members of Kerman University of Medical Sciences who had been selected by purposeful sampling method. For this purpose, 13 faculty members of Kerman University of Medical Sciences who were interested in the topic were interviewed. To collect data, a number of general questions were asked from the participants to clarify specific topics. The interviews lasted between 20 and 45 min. The descriptive phenomenology method was used for data analysis based on the Colaizzi's seven steps. RESULTS: In the present study, five main themes include; reforming the bureaucracy, paying attention to the empowerment of university personnel, improving the status of graduates, reviewing the status of education and research, and connecting with the industry and making a profit were identified. CONCLUSION: We can use strategies such as reduction of bureaucracy, privatization, reduction of management pyramid, culture building, creation of appropriate reward system, and taking a role model from successful people.

Genetic Basis for Variation in Wheat Grain Yield in Response to Varying Nitrogen Application.

Nitrogen (N) is a major nutrient needed to attain optimal grain yield (GY) in all environments. Nitrogen fertilisers represent a significant production cost, in both monetary and environmental terms. Developing genotypes capable of taking up N early during development while limiting biomass production after establishment and showing high N-use efficiency (NUE) would be economically beneficial. Genetic variation in NUE has been shown previously. Here we describe the genetic characterisation of NUE and identify genetic loci underlying N response under different N fertiliser regimes in a bread wheat population of doubled-haploid lines derived from a cross between two Australian genotypes (RAC875 × Kukri) bred for a similar production environment. NUE field trials were carried out at four sites in South Australia and two in Western Australia across three seasons. There was genotype-by-environment-by-treatment interaction across the sites and also good transgressive segregation for yield under different N supply in the population. We detected some significant Quantitative Trait Loci (QTL) associated with NUE and N response at different rates of N application across the sites and years. It was also possible to identify lines showing positive N response based on the rankings of their Best Linear Unbiased Predictions (BLUPs) within a trial. Dissecting the complexity of the N effect on yield through QTL analysis is a key step towards elucidating the molecular and physiological basis of NUE in wheat.

The Genetic Control of Grain Protein Content under Variable Nitrogen Supply in an Australian Wheat Mapping Population.

Genetic variation has been observed in both protein concentration in wheat grain and total protein content (protein yield). Here we describe the genetic analysis of variation for grain protein in response to nitrogen (N) supply and locate significant genomic regions controlling grain protein components in a spring wheat population. In total, six N use efficiency (NUE) field trials were carried out for the target traits in a sub-population of doubled haploid lines derived from a cross between two Australian varieties, RAC875 and Kukri, in Southern and Western Australia from 2011 to 2013. Twenty-four putative Quantitative Trait Loci (QTL) for protein-related traits were identified at high and low N supply and ten QTL were identified for the response to N for the traits studied. These loci accounted for a significant proportion of the overall effect of N supply. Several of the regions were co-localised with grain yield QTL and are promising targets for further investigation and selection in breeding programs.