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کاربرد نوع شرط:
- جایگاه : پژوهشی
- مجله: Asia Pacific Journal of Medical Toxicology
- نوع مقاله: Journal Article
- کلمات کلیدی: lead poisoning,Blood Lead level,Plumbism,Opium Smoking,Inhalation,Opium Ingestion
- چکیده:
- چکیده انگلیسی: Background: During the recent years, risk of lead poisoning has increased in Iranian’s opium users. A few researches showed that the most common route was ingestion of lead contaminated opium in these patients. However, data on lead poisoning through inhalation route in opium smokers is scarce. The aim of the current study was to determine lead poisoning in opium smokers.
Method: In this case-controlled study, blood lead level (BLL) and clinical lead poisoning were assessed and compared between pure inhalational and pure ingestionally chronic opium users and healthy controls.
Results: There were totally 90 cases, 30 patients in each group (pure inhaler opium users, pure oral opium users, and control group). In chronic opium users (case group), mean age of the patients was 48.91±13.14 yeas (range; 22 to 79 years). Eighty-four (85%) patients were male (male to female ratio: 5.6/1). Mean BLL was 10.6±4.2 and 126.1±52µg/dL in opium smokers and ingestional users, respectively (P=0.001). The mean of BLL in healthy control group was 4.78 µg/dL±1.83.
Conclusion: In contrast to chronic ingestion of opium, the probability of absorption of lead via lungs is low when opium used by smoking and inhalation route. So, lead toxicity is not common in acute or chronic inhalational users of lead-contaminated opium.- انتشار مقاله: 29-04-1398
- نویسندگان: Nader Rezaei,Pouyan Alinia,Abbas Aghabiklooei,Shirin Izadi
- مشاهده
- جایگاه : پژوهشی
- مجله: Advances in Mathematical Finance and Application
- نوع مقاله: Journal Article
- کلمات کلیدی: Artificial Neural Network,financial crisis,Genetic Algorithm
- چکیده:
- چکیده انگلیسی: Organizations expose to financial risk that can lead to bankruptcy and loss of business is increased nowadays. This may leads to discontinuity in operations, increased legal fees, administrative costs and other indirect costs. Accordingly, the purpose of this study was to predict the financial crisis of Tehran Stock Exchange using neural network and genetic algorithm. This research is descriptive and practical and in order to collect data Stock Exchange database software has been used. For data analysis, we used artificial neural network in base form and artificial neural network mix with genetic algorithm. In addition for methods comparison, determination coefficient, Mean squared error and Root-mean square error have been used. The result of study shows that the best artificial neural network is a network with a hidden layer and eight neurons in the layer. This network could predict 97.7 percent of healthy and bankrupt companies correctly for test data. Furthermore the best mixed neural network with genetic algorithm is a network with 400 replications and population size 50, one layer and eight neurons which could correctly predict 100% of healthy and bankrupt companies. Finally, comparison of results of two methods shows that the best method for predicting financial crisis is mixed neural network with genetic algorithm.
- انتشار مقاله: 14-12-1397
- نویسندگان: Nader Rezaei,Maryam Javaheri
- مشاهده
- جایگاه : پژوهشی
- مجله: Advances in Mathematical Finance and Application
- نوع مقاله: Journal Article
- کلمات کلیدی: Overreaction,Under-reaction,Behavioral Finance,Bayes' rule
- چکیده:
- چکیده انگلیسی: Stock market is affected by news and information. If the stock market is not efficient, the reaction of stock price to news and information will place the stock market in overreaction and under-reaction states. Many models have been already presented by using different tools and techniques to forecast the stock market behavior. In this study, the reaction of stock price in the stock market was modeled by the behavioral finance approach. The population of this study included the companies listed on the Tehran Stock Exchange. In order to forecast the stock price, the final price data of the end December, March, June, and September 2006-2015 and the stock prices of 2014 and 2015 were analyzed as the sample. In this study, Bayes' rule was used to estimate the probability of the model change. Through this rule, the probability of an event can be calculated by conditioning the occurrence or lack of occurrence of another event. The results of model estimation showed that there is the probability of being placed in high-fluctuated regimes (overreaction) and low- fluctuated (under-reaction of stock price despite the shocks entered to the stock market. In modelling with the 4-month final prices, it was proved that the real stock price had no difference from the market price.
- انتشار مقاله: 18-07-1397
- نویسندگان: Nader Rezaei,Zahra Elmi
- مشاهده