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Background: Iranian (Lahijan) black tea caffeine has been previously shown to have antifungal activity against Candida albicans. The aim of this study was to investigate whether the combination of caffeine and fluconazole (FLU) has an effective antifungal activity on a FLU-resistant (MIC >64mgL^-1) C. albicans PTCC5027. Materials and Methods: Caffeine from Lahijan black tea was extracted and its pharmacological effects against 20 clinical isolates of FLU-sensitive and resistant C. albicans was evaluated by Colony Forming Units (CFU) method. Furthermore, the synergistic effect of caffeine and FLU against PTCC-5027strain was investigated. Results: Our results indicate the antifungal efficacy of Lahijan black tea caffeine on C. albicans isolates and subsequent identification of caffeine in combination with FLU againstPTCC-5027 strain. The concentrations of caffeine causing 90% growth inhibition (MIC₉₀) for  PTCC-5027 strain, FLU-resistant and -sensitive C. albicans isolates were 25mgL^-1, 24.4mgL^-1 and 37.2mgL^-1,respectively. The combination of caffeine with FLU showed stronger antifungal activity against C. albicans PTCC5027. The addition of 12.5mgL^-1 caffeine to FLU 10-50 mgL^-1 (below MIC₉₀) inhibited the growth of C. albicans PTCC5027 by 99.3%–99.7%, the concentrations at which neither caffeine nor FLU alone affected the growth. Conclusion: It can be concluded that caffeine has antifungal effect on C. albicans and in combination with FLU can enhance the antifungal activity of FLU against C. albicans. The synergism of the combination of caffeine and FLU induces multiple antifungal effects, resulting in the use of lower doses of the FLU. It suggests that this can decrease the side effects of antifungal drugs.

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Background: This study aimed to assess the influence of video games on voice learning in students of speech therapy.
Methods & Materials: This study was a clinical trial study in which 102 fifth semester students of speech therapy group of Ahvaz Jundishapur University of Medical Sciences took part and were divided into two groups. The first group included 27students who were admitted in the university from 2008and2009 trained in traditional training and the second group (N = 75) who were admitted in 2010, 2011, 2012, and 2013 spent their traditional training plus using the software of Avaz-e-Ma. at the end of each semester. Students' satisfaction of the learning of each group was obtained through using the qualitative scale and the final exam of each group. The relationship between the learning type and the student scores was analyzed using Pearson correlation coefficient and the difference between of both groups were analyzed by independent T-test.
Results: The mean age of the first and the second group were 20.11 ± 3.02 and 20.25 ± 2.12 years old respectively. The mean score of the students who learned by software were 18 ± 0.2 and the students by traditional way was 12 ± 0.2 that was significant difference (P < 0.001). The majority of the students (90%) believed that the use of software has been useful.
Conclusion: The use of educational games in the classroom leads to an increase in the students' grades and the satisfaction of the students with the quality of instruction. Accordingly, using technology in educational system is recommended.

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Financial markets play a vital role in supplying and facilitating the flow of funds into production and industry sectors of economy and can result into the acceleration of economic growth. Indeed, many experts believe that the development of financial markets acts as the engine for growth. The main objective of this paper is analyzing the relationships between financial market development and economic growth through focusing on Iranian economy and thirteen other countries for the period 1988-2003. In this regard in addition to the Beck and Levin model (2003), we have used three versions of Granger–Casualty approach, Cointegartion test and panel data estimation procedure. Casualty test shows that in Iran, bank and stock market size have no strong effect on economic growth despite the fact that the effect of economic growth on stock market is positive and meaningful. The results of panel data estimation revealed that in real terms, investment and labor force, positively and strongly affect economic growth. In the money sector, the effects of banking system are statistically acceptable, although the positive effect of stock market is not statistically acceptable. The absence of Long–run co integration relation between financial markets and economic growth for the period 1976-2003 is the result of Auto-Regressive Distributed Lag Estimation. In sum, the long – run relation between money market and economic growth is negative and this true for the Iranian economy.

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Spectroscopy in visible and part of near infrared region was assessed as a non-destructive technique for the detection of plants infected with Potato virus Y (PVY). The aim of our research was to recognize spectral signatures that indicate PVY infected plants. In this assay, we studied spectral reflectance of potato leaves showing different PVY symptoms in cultivars Agria and Milva. Virus titer of leaves that showed different disease symptoms, were estimated using enzyme-linked immune sorbent assay. The means of spectral data obtained from different leaves in each experimental plant were used for spectral analysis. Analyses showed that spectral region in 900-1100nm was markedly sensitive to the PVY infection and could be useful for developing a good spectral signature for detection of the infection. Based on the X loading weights obtained from principal component analysis (PCA), sensitive wavelengths were screened, some wavelengths in this region have most positive or negative loading and based on linear discriminant analysis, they could discriminate infection status with high accuracy. The reflectance variation in this region is related to changes in cell structure and water activity due to viral infection. Results indicate that spectroscopy has a suitable potential to detect virus-infected plants; which could be further developed for more accurate potato field inspection aimed at controlling the spread of viral infection.
 

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Abstract
Aims: For the purpose of marketability and consumer preferences, two types of hand moisturizing products (Alginate gel and Fucoidan cream) produced from Sargassum algae, this study was conducted. then evaluated with a common commercial sample as a control.
Methods: Gel and two cream samples were prepared in 3 jars of 10 g to evaluate 30 individuals as panel members. Evaluation was performed using one product per week and with a one-week break between sessions. The designed questionnaire consisted of sociological questions and 12 characteristics of the products that were rated with 3 points of preference The Friedman test was used to analyze the ratings and the scoring method was used to identify the final product.
Results: Two characteristics of produced cream and gel (moisturizing and shelf life) at a significant level. The gel had the highest moisturizing capacity and the cream had the highest shelf life. Consumers paid more attention to the nourishing and hydrating properties of the skin, being organic and soft in choosing the suitable moisturizer for their hands. They like moisturizing cream of 250 gr jar. Nutrition and hydrating, therapeutic effect and skin repair were also ranked as high priority. Ultimately, the Fucoidan moisturizing cream gained the highest preference in market.
Conclusion: The Fucoidan cream produced from Sargassum algae compared to alginate gel from this alga, as a moisturizer with suitable shelf-life and have other hand cream properties, can be an acceptable commercial product in the market.
 

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Economic development is one of the major policies of a country which is concerned to industry and technology on one hand and leads to environmental pollution on the other hand. The experiences of developed countries show that economic development with emphasis on the industry sector, without any attention to environment, can create serious problem against sustainable development. Industrialization has caused increasing energy consumption and therefore air pollution. It's so important to consider the relationship between industrial activities and industrial pollution in developing countries, because industry sector has a basic role in development process of these countries. Therefore the aim of this study is examining and qualifying of linkage between industrial activity and air pollution, using an industry-level dataset of IRAN manufacturing industries during the period 1995-2007. The result of study shows that air pollution is a positive function of energy consumption, industrial activity and physical capital intensity and also is a negative function of labor productivity, fuel price and human skill intensity.

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One of the key concepts in risk managing of financial portfolios is the probability based risk measurement method known as value at risk. During recent years, various methods have been introduced by researchers to compute this criterion. Because of their dissimilar assumptions and procedures, making the use of each of which creates different results. Therefore, this paper uses two main methods in order to measure the value at risk of foreign exchange portfolio. They comprise generalized autoregressive conditional heteroskedasticity model and Monte Carlo Simulation. Using failure rate back testing, the results of these methods are compared. The results of the evaluation demonstrate that the mentioned methods have different performances.

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For this purpose, field study and data recording in two parts, and different environmental situation in one micro climate.
Material and method: crowded places were studied to 18 days from the first day of shahrivar to 18th of shahrivar; two categories were created: the first Baghe fin open spaces and the second historical textures open spaces. After finishing library studies, physical presence in the texture and conducting field study (observation, and data collection of site) simultaneously the responses of 788 of inhabitants and tourists to the questionnaires  (environmental and thermal situations), climate parameters (temperature, air flow speed, moisture, co, co₂) were recorded. Then the dress rate and the metabolism of people was computed with delta log10 software, and after collecting and analyzing the data with spss24 software, thermal comfort of respondents based on UTCI was determined by Ray Man software.
Findings: The finding shows that the respondents in the whole surrounding of the study experienced thermal comfort between 20,23 and 35,61 centigrade degree. Also thermal comfort scope in Baghe fin between 19,45 to 37,63 and in historical texture between 18,5 to 35,16 centigrade.
Conclusion:  The results of this study showed that the scope of thermal comfort in Baghe fin is higher the that of Kashan historical texture about 1,52 centigrade.

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To meet excellency and to do continuous improvement are among the main challenges for modern organizations to live in competitive market. Excellency models help organizations to satisfy essential needs of society and customers in the best possible way. To compare themselves with their competitors, organizations need to have well organized and reliable procedure in hand to make decisions based on this comparison. In this paper, first, the Excellency models were stndied and then auto maker companies were ranked on Excellency level using PROMRTHEE method. The main goals of this paper were: recognition of the Excellency level of auto maker companies, ranking them using PROMETHEE method and finally introducing this method as one of the powerful multi attribute decision making methods for future applications.

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Objective: In this study the susceptibility of Candida albicans to inhibitory effect of polyphenols under varying time (24 and 48 hours) conditions were evaluated. Materials and Methods: Green tea leaf polyphenols were extracted and analyzed by chromatography. Among polyphenols, Catechin showed stronger antifungal activity against C. albicans PTCC-5027. Catechin's MIC90 (The concentration of Catechin causing 90% growth inhibition of tested strain of C. albicans) and MFC (The minimum antifungal susceptibility of Catechin) were determined by Macro dilution test and calculation after 24 and 48 hours. Results: The antifungal activity of Catechin was time dependent. Catechin's MIC for 0.5×10³, 1×10³ and 2×10³ cells/ml was 12.5, 25 and 100 mg/ml after 24h respectively. The results after 48h for 0.5×10³, 1×10³ and 2×10³ cells/ml were 6.25, 12.5 and 25 mg/ml respectively. Fluconazol was tested on C. albicans PTCC-5027 and the results indicated that this strain of Candida is fluconazol resistant. Data shown are from three separate experiments and were analysed statistically. Conclusion: C. albicans PTCC-5027 is fluconazol resistant, however green tea leaf polyphenols especially Catechin could inhibit the growth of this yeast at MIC and MFC concentrations. On the basis of the obtained results the green tea leaf contains effective antifungal components. Since the common and generic antifungal drugs possess some side effects and also there is an increasing drug resistance, it is hoped that consumption of herbal drugs may help to cure fungal diseases and to avoid the side effects of antimycotics as a good replacement.

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Ramsey model is one of the most important basic models to study intertemporal resource allocation. This model is derived from microeconomic optimal principle so it has a key role in macroeconomics with micro foundations. Hence, in many economic researches it is considered as a reference theory. Application of this model in economy of Iran will provide an appropriate theorem framework for explaining empirical facts of the Iranian economy and will introduce a new approach to researchers. The main idea of this study is generalizing Ramsey model through including terms of trade and its calibration in the economy of Iran. For this purpose first, the model is explained. Then, the first order condition is derived and mathematical optimal path of variables is solved.  Finally, the model is calibrated by GAMS package for economy of Iran in time period (2006-2036). The results indicate that there is a feasible solution for model and the optimal path of variables can be observed. The optimal path of Gross National Production and Consumption are increasing but the optimal path of capital stock and investment is primarily increasing then decreasing. In the final section of this paper a sensitivity analysis is presented. Some scenarios are designed for the important parameters of model like time preferences rate, intertemporal substitution elasticity of consumption, labour growth rate and output elasticity of capital. Sensitivity analysis shows that output elasticity of capital and labour growth rate increased the social welfare and shifted optimal path of variables upward. But time preferences rate and intertemporal substitution elasticity of consumption had inverse effect on social welfare and optimal path of variables.

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Tourism plays a growing role in developing countries and is considered as a way of government deficit reduction, gaining foreign exchange and creating jobs. In addition, it is viewed as a channel of getting away from single product economies. In fact, tourism is an industry with multi-dimensional impacts on different sectors of economy. Therefore, it can also be viewed as an important development factor in Isfahan province. In this study, the impacts of international tourist expenditures on income generation, allocation, distribution, consumption and savings in different economic sectors of Isfahan province has been analyzed using Social Account Matrix (SAM) technique, supported by input-output matrix. The results show that financial sector has a very poor performance in this regard in terms of generating revenues coming from international tourists. Although the government sector has the highest share regarding the initial allocation of income, but due to the transactions happening among structural sectors, households have been the main gainers of this income generation. In fact, almost 84% of the generated revenues in this way have been consumed.

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Parkinson's disease (PD) is the second most common neurodegenerative disease after Alzheimer's disease and the prevalence of it has increased worldwide. PD causes severe damage to loss of midbrain dopaminergic neurons (DN) at substantia nigra which involves in the movement control. The synaptic terminals of DNs are destroyed in the posterior putamen. PD is also characterized by accumulation of misfolded and amyloid α-synuclein into proteinous inclusions named Lewy bodies. So far there is no effective treatment for PD and approved medications for PD can only slow down clinical progression, control motor and non-motor symptoms. Currently, the approved medications just induce the release of dopamine and prevent the release of acetylcholine from nerve terminals of caudate cholinergic interneurons and it is necessary to provide more effective treatment methods in the early stages of the disease. Significant progress has been achieved in development of drugs that can reduce neuronal cell death and lead up to neuroprotection, however targeting delivery of drugs to improve the pharmaceutical effects of drugs is remained as a challenge. Therefore, there is a pressing demand to find practical strategies for delivering these pharmaceuticals in vivo through the BBB without disrupting the brain's functions. In this regard, Focused ultrasound (FUS) technology eliminates the need for brain surgery and temporarily opens the blood-brain barrier to allow drugs to pass through. In this review, the application of FUS as a new drug delivery application in the PD models and the potential clinical application of neuroprotective agents are provided briefly.
 

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Objective: Aflatoxin is important in the food industry, in animal husbandry and the medical area; there are enormous negative economic impacts due to this toxin. Numerous studies have researched extracts and plant compounds with the intent to reduce the growth of aflatoxin-producing organisms, inhibit toxin production and suppress the major toxin encoded genes (i.e., aflR) in these organisms. Licorice is an important plant in traditional medicine that possesses numerous antimicrobial activities. There is no report regarding the effects of licorice or its mechanism of action on the aflatoxin-producing Aspergillus species. The present study focuses on the inhibitory effects of licorice extract on aflR gene expression and the growth and survival of Aspergillus parasiticus (A. parasiticus). Methods: After the culture of A. parasiticus in toxin-inducer medium, we measured the minimal inhibitory concentration (MIC) for licorice extract. The aflatoxin concentration in the control and treated media was determined by HPLC. After harvesting the fungi from the toxin-inducing medium, its mRNA was extracted and cDNA synthesized by universal primers. The quantitative change in the aflR expression was analyzed via real-time PCR. Statistical analysis was performed by SPSS (v16). Results: The production of fungal mycelium decreased with increasing concentrations of licorice extract. The highest inhibitory concentration observed was 500 mg/ml of the extract. HPLC analyses revealed that the 10 mg/ml concentration of licorice extract inhibited toxin production by 99.9%. At this concentration, aflR gene expression was suppressed up to 40% as documented by quantitative RT-PCR analysis. Conclusion: Overall we concluded that the Licorice extract could inhibit the aflR gene expression and consequently the aflatoxin production efficiently in the A. parasiticus.

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Objective: In recent decades, β-glucans have been used as important complementary and alternative medicines for numerous immunocompromised individuals and those with end stage of cancer terminal. The most active form of β-glucans is β(1,3)D-glucan and its  most common source is cell wall of Candida albicans. Recently it has been introduced as a nano particle design to be used as a carrier for drug delivery. The current study researches a rapid method for the extraction of β(1,3)D-glucans. Methods: The present study was conducted atTarbiatModaresMedicalUniversity in 2012. Candida solubilized β-glucans were obtained by oxidation of the cell wall with sodium hypochlorite and sodium hydroxide. The particle part could be solubilized by treatment with dimethylsulfoxide (DMSO) and zymolyase digestion to extract β(1,3)D-glucan. The soluble fractions were lyophilized. We performed the Callose test to verify the presence of β(1,3)D-glucans. Solubilized fractions were dissolved in D2O and 1H-NMR spectra were measured. Results: The soluble β(1,3)D-glucan fraction which was derived from 1 g of dried Candida albicans germ tube weighed 190 mg. β(1,3)D-glucan was verified by the Callose test and ¹H-NMR test compared with Curdlan (standard). ¹H-NMR spectra verified the existence of β(1,3)D-glucan in the final product. Conclusion: In the present study, extraction of β(1,3)D-glucan by oxidation of the cell wall using sodium hypochlorite yielded more pure β(1,3)D-glucans in comparison with other extraction methods. Thus it might represent a rapid method of extraction.

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The purpose of this study is to investigate the performance of budget designers in forecasting government revenues in the Iranian economy. For this purpose, three methods, including analysis with statistical indicators, equation of error component separation, and macroeconomic regression model have been used in order to analyze the prediction errors in tax, oil and gas revenues, and income from property and sale of public goods and services during 1973-2011. The results show that forecasts of all government revenues by budget designers were optimistic (over-estimated), on average, and the highest forecasting errors belonged to revenues from government ownership. The results of the second method show that the forecasting errors in four kinds of government revenues have been mainly nonsystematic and influenced by exogenous shocks and factors.  Furthermore, the results of the third method, in which the factors affecting prediction of government revenue were evaluated using the seemingly unrelated regression equations (SURE), show that the non-oil GDP and the exchange rate had significant effects on the forecast of all government revenues. However, inflation and unemployment rates were effective only in predicting tax revenue and income from the sale of goods and services.