Validation of the adapted response to stressful experiences scale.

There is evidence to suggest that resilience may be a protective factor to moderate the experience of mental health symptoms among military personnel. The present study analyzed the validity and reliability of a full-scale and adapted measure of resilience from a sample of 470 U.S. military service Veterans receiving clinical services from a civilian nonprofit agency. Results of an exploratory factor analysis, a two-factor confirmatory factor analysis, and a single-factor confirmatory factor analysis indicated that while the Response to Stressful Experiences Scale (RSES) indicated a fair model fit for the sample, the brief measure of resilience (RSES-4) demonstrated a better factor structure (RMR = .017, GFI = .995, CFI = .994, TLI = .981, RMSEA = .057), criterion and concurrent validity, and acceptable internal consistency.

Agent-based modeling of participants' behaviors in an inter-sectoral groundwater market.

While being affected by economic and hydrological conditions, the behaviors of water market participants can also be caused by their psychological characteristics and social stimuli of the environment. This paper employs agent-based modeling (ABM) approach to simulate a local groundwater market in central Iran. The proposed ABM framework couples social, economic, and hydrological sub-models. The social sub-model benefits from the theory of planned behavior under field studies to design psychology-based behaviors of trading agents. Moreover, in continuous interaction with the FlowLogo hydrological sub-model, the economic sub-model simulates the inter-sectoral water trading under a double-auction mechanism. The inter-sectoral trading includes selling the farms' irrigation water to the industry sector. The calibration and validation results for an eight-year simulation period (2010-2018) confirm the acceptable performance of the proposed ABM framework. Water trading patterns experience relatively extreme variations in the first years. However, with the adaption of the agents' bids to the market conditions, they gradually emerge in a more stable form in the last years. Furthermore, updating the psychological factors increases the agents' intention of participating in the market, and thus, the competition level over time. Finally, the hydro-economic analysis reveals that implementing the dynamic cap-and-trade policy increases the total net benefits of market participants by an average of 27% per year while reducing the region's groundwater drawdown by 56 cm. Such inter-sectoral water markets can help with the sustainable exploitation of groundwater resources.

Application of non-cooperative dynamic game theory for groundwater conflict resolution.

The opposing objectives of the groundwater stakeholders, ranging from maximum withdrawal for economic gain to minimum withdrawal for aquifer and environmental protection, lead stakeholders to behave non-cooperatively. In this study, dynamic non-cooperative games are applied to model these conflicts. These games incorporate stakeholders' non-cooperative decision-making processes and groundwater exploitation details over time. The two key players considered in this study are the government, which aims to minimize the groundwater drawdown, and local farmers, who pursue maximum economic gain. In order to calculate the players' payoffs over the modeling period, a simulation-optimization model is developed. For evaluation, the proposed methodology is implemented in the Bad-Khaledabad study area in Iran. Therefore, two dynamic non-cooperative games are developed, considering weak governmental power and players' interaction. It is concluded that creating a transactional relationship, involving the cropping patterns changes and the irrigation efficiency enhancement, will increase farmers' profits by 28% and decrease withdrawal from the aquifer by 21%.

The anti-tumor activity of exopolysaccharides from Pseudomonas strains against HT-29 colorectal cancer cell line.

The anti-tumor activity of extracted exopolysaccharides (EPSs) (without any side effects) of Pseudomonas aeruginosa on HT-29 colorectal cancer cell line has not been previously investigated. The extraction and partial characterization of EPS from the strains of P. aeruginosa including A (CIP A22(PTCC1310)), and B (a clinical strain) were performed. The 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and sulphorhodamine B (SRB) assays as well as microscopy were used to estimate the cell viability and morphological changes in HT-29 cells subjected to EPS at 0, 7.6, 15.8, 31.2, 62.5 and 125 µg/ml. The apoptotic effects of EPS were also examined by flow cytometry. The EPSs were found to be cytotoxic against HT-29 cells with IC50 values at 44.8 (EPS-A) and 12.7 (EPS-B) µg/ml. The counteraction of 125 µg/ml of EPS-A (87.5 and 56.7%) and EPS-B (86.7 and 59.2%) resulted in the highest repressive rates using the MTT and SRB assays, respectively. Flow cytometric results showed that EPS-A and EPS-B could induce apoptosis (33% and 39%) and necrosis (65% and 59%). The extracted EPSs of both bacterial strains can be used as natural, effective, efficient and anti-cancer drugs. However, more characterization at molecular and structural levels in this respect may be required.

Author Correction: The future of extreme climate in Iran.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The future of extreme climate in Iran.

Iran is experiencing unprecedented climate-related problems such as drying of lakes and rivers, dust storms, record-breaking temperatures, droughts, and floods. Here, we use the ensemble of five high-resolution climate models to project maximum and minimum temperatures and rainfall distribution, calculate occurrences of extreme temperatures (temperatures above and below the historical 95th and 5th percentiles, respectively), analyze compound of precipitation and temperature extremes, and determine flooding frequencies across the country. We found that compared to the period of 1980-2004, in the period of 2025-2049, Iran is likely to experience more extended periods of extreme maximum temperatures in the southern part of the country, more extended periods of dry (for ≥120 days: precipitation <2 mm, Tmax ≥30 °C) as well as wet (for ≤3 days: total precipitation ≥110 mm) conditions, and higher frequency of floods. Overall, the combination of these results projects a climate of extended dry periods interrupted by intermittent heavy rainfalls, which is a recipe for increasing the chances of floods. Without thoughtful adaptability measures, some parts of the country may face limited habitability in the future.

Assessment of input data selection methods for BOD simulation using data-driven models: a case study.

Using the multivariate statistical methods, this study interprets a set of data containing 23 water quality parameters from 10 quality monitoring stations in Karkheh River located in southwest of Iran over 5 years. According to cluster analysis, the stations are classified into three classes of quality, and the most important factors on the whole set of parameters and each class are determined by the help of factor analysis. The results indicate the effects of natural factors, soil weathering and erosion, urban and human wastewater, agricultural and industrial wastewater on water quality at different levels and any location. Afterwards, five input selection methods such as correlation model, principal component analysis, combination of gamma test and backward regression, gamma test and genetic algorithm, and gamma test by elimination method are used for modeling BOD, and then their efficiency is investigated in simulation BOD with local linear regression, Artificial Neural Network, and genetic programming. From five methods of input variables in BOD simulation by local linear regression, genetic test and backward regression with RMSE error of 0.27 are the best input methods; gamma test based on genetic algorithm is the best model in simulation by Artificial Neural Network with RMSE error of 0.28, and finally, the gamma test model based on genetic algorithm with RMSE error of 0.1303 is the most appropriate model in simulation with genetic programming.

Effluent trading in river systems through stochastic decision-making process: a case study.

The objective of this paper is to provide an efficient framework for effluent trading in river systems. The proposed framework consists of two pessimistic and optimistic decision-making models to increase the executability of river water quality trading programs. The models used for this purpose are (1) stochastic fallback bargaining (SFB) to reach an agreement among wastewater dischargers and (2) stochastic multi-criteria decision-making (SMCDM) to determine the optimal treatment strategy. The Monte-Carlo simulation method is used to incorporate the uncertainty into analysis. This uncertainty arises from stochastic nature and the errors in the calculation of wastewater treatment costs. The results of river water quality simulation model are used as the inputs of models. The proposed models are used in a case study on the Zarjoub River in northern Iran to determine the best solution for the pollution load allocation. The best treatment alternatives selected by each model are imported, as the initial pollution discharge permits, into an optimization model developed for trading of pollution discharge permits among pollutant sources. The results show that the SFB-based water pollution trading approach reduces the costs by US$ 14,834 while providing a relative consensus among pollutant sources. Meanwhile, the SMCDM-based water pollution trading approach reduces the costs by US$ 218,852, but it is less acceptable by pollutant sources. Therefore, it appears that giving due attention to stability, or in other words acceptability of pollution trading programs for all pollutant sources, is an essential element of their success.

A decision-making framework for river water quality management under uncertainty: Application of social choice rules.

An important issue in river water quality management is taking into account the role played by wastewater dischargers in the decision-making process and in the implementation of any proposed waste load allocation program in a given region. In this study, a new decision-making methodology, called 'stochastic social choice rules' (SSCR), was developed for modeling the bargaining process among different wastewater dischargers into shared environments. For this purpose, the costs associated with each treatment strategy were initially calculated as the sum of treatment cost and the fines incurred due to violation of water quality standards. The qualitative simulation model (QUAL2Kw) was then used to determine the penalty function. The uncertainty associated with the implementation of strategies under the economic costs (i.e., the sum of treatment and penalty costs) was dealt with by a Monte-Carlo selection method. This method was coupled with different social choice methods to identify the best solution for the waste load allocation problem. Finally, using the extended trading-ratio system (ETRS), the most preferred treatment strategy was exchanged among dischargers as the initial set of discharge permits aimed at reducing the costs and encouraging dischargers to participate in the river water quality protection scheme. The proposed model was finally applied to the Zarjoub River in Gilan Province, northern Iran, as a case study. Results showed the efficiency of the proposed model in developing waste load allocation strategies for rivers.

The effective factors on the academic progress of the students of Tehran University of Medical Science.

OBJECTIVE: To examine factors influencing the academic performance of students at Tehran University of Medical Sciences. METHODS: The retrospective cross-sectional study was conducted between 2008 and 2009 at the Tehran University of Medical Sciences, Iran. Data was obtained from the education office of the university and SPSS version 15 was used for data analysis. RESULTS: Of the 670 students in the study, 230 (34.3%) were boys and 440 (65.6%) were girls.The highest mean score of courses belonged to the Psychiatry Institute (18.68) and the lowest was in the School of Medicine (15.20). Twenty nine per cent of students had failed course and 8.4% had failed semester. CONCLUSION: The variables gender, level of education, and school are the most important factors affecting the educational progress of students. Overall, students' failure ratios varied significantly between schools and educational levels.

Relationship between Personality Profiles and Suicide Attempt via Medicine Poisoning among Hospitalized Patients: A Case-Control Study.

Objectives. Inflexible personality traits play an important role in the development of maladaptive behaviors among patients who attempt suicide. This study was conducted to investigate the relationship between personality profiles and suicide attempt via medicine poisoning among the patients hospitalized in a public hospital. Materials and Methods. Fifty-nine patients who attempted suicide for the first time and hospitalized in the poisoning ward were selected as the experimental group. Sixty-three patients hospitalized in the other wards for a variety of reasons were selected as the adjusted control group. Millon Clinical Multiaxial Personality Inventory, 3rd version (MCMI-III) was used to assess the personality profiles. Results. The majority of the suicide attempters were low-level graduates (67.8% versus 47.1%, OR = 2.36). 79.7% of the suicide attempters were suffering from at least one maladaptive personality profile. The most common maladaptive personality profiles among the suicide attempters were depressive personality disorder (40.7%) and histrionic personality disorder (32.2%). Among the syndromes the most common ones were anxiety clinical syndrome (23.7%) and major depression (23.7%). Conclusion. Major depression clinical syndrome, histrionic personality disorder, anxiety clinical syndrome, and depressive personality disorder are among the predicators of first suicide attempts for the patients hospitalized in the public hospital due to the medicine poisoning.

Groundwater vulnerability assessment using fuzzy logic: a case study in the Zayandehrood aquifers, Iran.

Groundwater is an important source of water, especially in arid and semi-arid regions where surface water is scarce. Groundwater pollution in these regions is consequently a major concern, especially as pollution control and removal in these resources are not only expensive but at times impossible. It is, therefore, essential to prevent their contamination in the first place by properly identifying vulnerable zones. One method most commonly used for evaluating groundwater pollution is the DRASTIC method, in which the Boolean logic is used to rank and classify the parameters involved. Problems arise, however, in the application of the Boolean logic. In this paper, the fuzzy logic has been used to avoid the problems. For this purpose, three critical cases of minimum, maximum, and mean values have been considered for the net recharge parameter. The process has been performed on the Zayandehrood river basin aquifers. The fuzzy-DRASTIC vulnerability map thus obtained indicates that the western areas of the basin generally have the maximum pollution potential followed by the areas located in the east. The central parts of the study area are found to have a low pollution potential. Finally, two sensitivity analyses are performed to show the significance of each value of the net recharge parameter in the calculation of vulnerability index.

Estimation of hazard function and its associated factors in gastric cancer patients using wavelet and kernel smoothing methods.

BACKGROUND AND OBJECTIVES: Increase of mortality rates of gastric cancer in Iran and the world in recent years reveal necessity of studies on this disease. Here, hazard function for gastric cancer patients was estimated using Wavelet and Kernel methods and some related factors were assessed. MATERIALS AND METHODS: Ninety- five gastric cancer patients in Fayazbakhsh Hospital between 1996 and 2003 were studied. The effects of age of patients, gender, stage of disease and treatment method on patient's lifetime were assessed. For data analyses, survival analyses using Wavelet method and Log-rank test in R software were used. RESULTS: Nearly 25.3% of patients were female. Fourteen percent had surgery treatment and the rest had treatment without surgery. Three fourths died and the rest were censored. Almost 9.5% of patients were in early stages of the disease, 53.7% in locally advance stage and 36.8% in metastatic stage. Hazard function estimation with the wavelet method showed significant difference for stages of disease (P<0.001) and did not reveal any significant difference for age, gender and treatment method. CONCLUSION: Only stage of disease had effects on hazard and most patients were diagnosed in late stages of disease, which is possibly one of the most reasons for high hazard rate and low survival. Therefore, it seems to be necessary a public education about symptoms of disease by media and regular tests and screening for early diagnosis.