In the present research, the equilibrium data of ternary systems, carbon dioxide- toluene- naphthalene is determined by using a high-pressure apparatus. Mentioned data is measured between 298.15 K and 308.15 K and pressure at 9.6 to 75.6 bar. In each experiment, equilibrium solubilities of naphthalene in toluene decrease by increasing the pressure due to adding the carbon dioxide as the anti-solvent. Also, the obtained experimental data have correlated by the Soave-Redlich-Kwong equation of states along with Van der Waals 1 and 2 mixing rules.The adjustable parameters of mentioned models are obtained using the experimental data and reported along with average absolute relative deviation of each model. The results show that SRK equation of state with vdW2 mixing rule (AARD=11.75 %) has less deviation than SRK-vdW1 (AARD=14.41 %) and optimum operational condition for production of fine particles (over than 90%) in the GAS process has been suggested.

Measurement of sulfur compounds in the tail GAS flow in the sulfur recovery unit is necessary in order to fine control the combustion furnace airflow and efficiency enhancement. In this research, required equations for calculation of air demand in feedforward and feedback control loops in the sulfur recovery unit of Ilam GAS Treating Plant are developed. First, the process was simulated. Then, using MLP neural network and nonlinear regression, K factor was determined for tail GAS analyzer air demand calculation. Total required air is sent to the combustion furnace through two lines: trim and main, such that 92. 5% of air is passed through the main line. Meanwhile, tail GAS analyzer air demand is in the range of-5 to +5 % of the total required air. The presented equations in this research can be employed for other sulfur recovery units.

Background & Aims: Liver cancer is one of the deadliest cancers and the most common cancers worldwide. Nanoparticles due to their wide applications in diagnostics, imaging and drug delivery, have attracted significant attentions (6). Upon a previous studies, the green-route mediated production of metal nanoparticles inhibits the progression of cancer cell lines (9, 10). Inprevios study the inhibition of the breast cancer cells were conducted by silver chloride nanoparticles synthesized by Onopordum acanthium L. extract through inducing apoptosis pathway (11). Lnc RNA GAS5 is a tumor suppressor, it’s an expression in some malignant tumors decrease. In liver Cancer Cells (HCC) The GAS5 gene Expression is reduced, which identifies the poor prognosis of this gene (5). However, a limited number of reports have been investigated on the cytotoxic effect of silver chloride nanoparticles on cancer cells, so in this study, we aimed to investigate it. In our study, we investigated the silver chloride nanoparticles synthesized by O. acanthium L. extract, as well as its anticancer effects on liver cancer and normal cell lines. The aim of this study was investigating the cytotoxicity effect of silver chloride nanoparticles and evaluation of LncRNA GAS 5 gene expression in liver cancer cells. Methods: Brifly, 100 mL of a solution of 1 mM silver nitrate was prepared in distilled water. Then, 5 mL of solution of O. acanthium L. extract (4 mg/mL) and KCl salt (1 mM) were drop wise added to the stirred silver nitrate solution. Subsequentely, the resulted solution was stirred at room temperature for 24 hours. This solution was then centrifuged at 13,000 rpm for 10 minutes; the supernatant was discarded and then centrifuged again with distilled water (11). In this study, HepG2 and HEK293 cells were obtained from the Pasteur Institute Cell Bank of Tehran and treated with silver chloride nanoparticles after 24 hours. Cell viability percentage of nanoparticles were determined by MTT (3-(4, 5-Dimethyltetrazollium Bromide) assay toward HepG2 and HEK293 cells. The HepG2 and HEK293 cell lines were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM) (Gibco, Scotland) medium with 10% FBS serum and 1% streptomycin antibiotic (Gibco, Scotland). The cells were then stored at 37 ° C with 5% CO2 in a humidified cell culture. To evaluate the in vitro cell viability, the colorimetric MTT method was assessed for investigating the appropriate lethal dose of silver chloride nanoparticles. Afterward, they were treated with silver chloride nanoparticles in various concentrations (0, 3.125, 6.25, 12.5, 25, 50, 100, 200 and 400 mg/mL) for 24 hours. Nanoparticles were added to the cells (1 × 104 cells per well) cultured on 96-well plate, which were incubated an overnight at 37 °C. Thereafter, MTT solution (100 μl of 0.05 mg/well) was added to the plate. Subsequently, dimethyl sulfoxide (DMSO) solvent we added of to each well to solubilize the formazan crystals. Finally, the optical density of the treated and untreated cells was evaluated with the ELISA reader (Eppendorf, Germany) at the wavelength of 570 nm. Finally, the viability of the cells was calculated according to the following formula: percentage of cell viability (%) = OD value of sample / OD value of control × 100. Levels of LncRNA GAS5 gene expression in HepG2 liver cancer cell were quantified using quantitative real-time reverse transcription-PCR (qRT-PCR) technique. To assess the qRT-PCR method, total cellular RNA extraction was carried out using the RNA extraction kit based on to the instructions in the Qiagen kit (Qiagen, Germany). To synthesis of transcriptional complementary DNA (cDNA), PrimeScriptTM RT Kit (Takara, Japan) was carried out (12). GAS5 and GAPDH primers were then conducted using NCBI primer blast in this study (Table 1). Subsequently, qRT-PCR method was evaluated by 100 ng of cDNA, SYBER Green PCR Master Mix (2X), followed by 2mM each of reverse and forward primers in final volume to 20 mL with nuclease free water. Also, the data was investigated by ABI StepOne using the Applied Biosystems qRT-PCR (ABI 7300 system, Applied Biosystems). Statistical significance between treatment and untreated groups were evaluated by One-way analysis of variance (ANOVA) with SPSS software version 22 and the Tukey post hoc. Data were expressed as mean ± the standard deviation of three replicates from three independent experiments. and P ˂0.05 was considered significance level. Results: The results showed that silver chloride nanoparticles decrease significantly the cell viability of cancerous HepG2 cells as compared to normal HEK293 cell line. In this regard, silver chloride nanoparticles were able to increase cell toxicity in a dose-dependent manner, as shown in Figure 1 and 2. Also, IC50 concentration of silver chloride nanoparticles toward HepG2 and HEK293 cells was 49 and 160 μg/mL, respectively. To conduct the effect of IC50 dose of nanoparticles on cell lines, we investigated HepG2 and HEK293 cells treated with 0, 3.125, 6.25, 12.5, 25, 50, 100, 200 and 400 mg/mL of nanoparticles for overnight using MTT assay. At concentration of 12.5, 25, 50, 100, 200, and 400 µg/mL of silver chloride nanoparticles, the viability of HepG2 was reduced to (79.85±6.44 )%, (63.68±7.05) % ,(46.87 ± 4.7)% , (31.83 ± 4.44)% , (18.63± 6.1) %, and (18.63± 6.1) (P < 0.001), respectively (Figure 1). At concentration of 50, 100, 200, and 400 µg/mL of silver chloride nanoparticles, the viability of HEK293 was reduced to (80.28±6.1 )%, (69.91±6.13) % ,(43.67 ± 7.76)% , and (24.99 ± 4.42)% (P < 0.001), respectively (Figure 2). In order to determine the effect of silver chloride nanoparticles on cancerous cells, alterations in the mRNA expression levels of LncRNA GAS5 gene in HepG2 cells were carried out using qRT-PCR technique followed by the exposure to nanoparticle. According to our study, the results of real time PCR displayed that the expression of LncRNA GAS5 was up-regulated by a 4.6±0.34 (p˂0.001) fold as compared to control gene. Conclusion: In summary, the effect of silver chloride nanoparticles against HepG2 and HEK293 cells showed that these nanoparticles have high cytotoxicity. Also, increase in LncRNA GAS5 gene expression level reveals the triggering apoptosis in HepG2 cells. silver chloride nanoparticles can be considered as a promising strategy for the treatment of liver cancer. Thus, for the liver cancer therapy, further in vivo investigations are required to determine the efficacy of the silver chloride nanoparticles.

The main purpose of this study is to investigate the effect of food price uncertainty on food security in Iranian households during the period 1981-2018 in a nonlinear model. To estimate uncertainty, the Generalized Autoregressive Score Model, and to estimate the effect of food price uncertainty on food security, the Smooth Transition Autoregressive model has been used. The results show that food price uncertainty in the first regime (low level of investment in agriculture) has a negative and significant effect and in the second regime (high level of investment in agriculture) has a negative and non-significant effect on food security. In the first regime, where the level of investment in the agricultural sector is below the threshold, as food price fluctuations increase, market uncertainty increases and signals with less transparency to producers and consumers. Under these circumstances, consumers will face the problem of reduced purchasing power and insecurity in access to food, which has a negative impact on food security. While, in the second regime and increasing the level of investment in the agricultural sector, the negative effects of uncertainty on food security can be partially offset. According to the results of the present study, officials should take effective steps on one hand, by prioritizing the financing of investment in the agricultural sector and facilitating the conditions of activity of the private and cooperatives sector in this field like moving from traditional to industrial agriculture. On the other hand, to reduce the price gap, regulate the market demand of agricultural products, and create conditions for food price stability, create a kind of protection against short-term fluctuations and shocks.

Static headspace combined with GAS chromatography/mass spectrometry is a powerful technique which can be used for separation and identification of volatile organic compounds in complex and different matrices such as soil, water, blood, urine, milk, cheese and especially yogurt. After sample collection, they were analyzed by HS-GC/MS system and the components (acetaldehyde, acetone, butanone and acetic acid) were detected and quantified. The limit of detection (LOD) was 100 ng/kg with selected ion monitoring (SIM) mode at m/z =60 for acetic acid. The relative standard deviation (RSD) was measured at 5.5% for acetic acid.

Predicting returns with the least error is one of the most important issues in financial markets that has been considered by many researchers in recent decades . Traditional linear and nonlinear models due to the inefficiency of linear models in market turbulence, the lack of correct extraction of the conditional distribution form of data due to the failure to record the conditional distribution dynamics in nonlinear models and the existence of limiting assumptions, it lacks the ability to predict returns in different market conditions. In order to eliminate the disadvantages of traditional models, in the present study using a new time-variable method called generalized autoregressive score (GAS) in order to predict the distribution of return of the total index of the stock exchange during the period 2010 to 2020 and for Bitcoin during the period 2014 to 2020. The results of modeling for the two assets by the new GAS model are compared with the results of the GARCH and AR models and their performance is tested for inside and outside the sample. The results show that in order to predict the daily return, the overall index of the new GAS model has a better performance and in order to predict the daily return of bitcoin, the GARCH model has been preferred.