Developing tools for determination of parameters involved in CO₂ based EOR methods

To mitigate the effects of climate change, CO₂ reduction strategies are suggested to lower anthropogenic emissions of greenhouse gasses owing to the use of fossil fuels. Consequently, the application of CO₂ based enhanced oil recovery methods (EORs) through petroleum reservoirs turn into the hot topic among the oil and gas researchers. This thesis includes two sections. In the first section, we developed deterministic tools for determination of three parameters which are important in CO₂ injection performance including minimum miscible pressure (MMP), equilibrium ratio (Kᵢ), and a swelling factor of oil in the presence of CO₂. For this purposes, we employed two inverse based methods including gene expression programming (GEP), and least square support vector machine (LSSVM). In the second part, we developed an easy-to-use, cheap, and robust data-driven based proxy model to determine the performance of CO₂ based EOR methods. In this section, we have to determine the input parameters and perform sensitivity analysis on them. Next step is designing the simulation runs and determining the performance of CO₂ injection in terms of technical viewpoint (recovery factor, RF). Finally, using the outputs gained from reservoir simulators and applying LSSVM method, we are going to develop the data-driven based proxy model. The proxy model can be considered as an alternative model to determine the efficiency of CO₂ based EOR methods in oil reservoir when the required experimental data are not available or accessible

The effect of spiritual interventions on the quality of life among patients with common cancers in southwest Iran

Spirituality, sometimes referred to as spiritual health, refers to believing in the existence of an entity or power beyond material life, developing an in-depth sense of unity or attachment to the universe. This study was conducted to investigate the effect of spiritual teachings on life expectancy and quality of life among patients with common cancers in Chaharmahal and Bakhtiari province, southwest Iran.Pretest-posttest on 200 people with different type of cancer in Chaharmahal va Bakhtiari. First, the questionnaires of quality of life and life expectancy were used to gather the patients’ data. Then, healthy lifestyle from the Quran perspective was taught to the people by a psychologist, a counselor, and a clergyman. 8 weeks after completion of the teachings, the questionnaires were re-administered to the patients. The data were analyzed by descriptive statistics (including mean and standard deviation) and analytical statistics (paired t-test).The results showed that the intervention had no effect on the quality of life in these patients (P>0.05). Moreover, there was not significant effect of the intervention in relation to life expectancy statistics before and after the intervention (P=0.857).The inconsistency between the findings of this study and those of other studies, confirming religion's effect in promoting the quality of life and life expectancy, may be attributed to the difference in the methods, study population, and sample size among the works, or high level of religious beliefs among patients with different type of cancer in Chaharmahal va Bakhtiari province

Reducing chronic medical complications due to failure of patient safety using Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) method

BACKGROUND: Human errors in the medical profession can lead to irreparable errors in people's lives, damage, and heavy costs. Among health care workers, nurses spend more time with patients compared to other personnel; hence, they are more prone to human error. Therefore, the purpose of this study was to identify and evaluate human errors using the Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) method in nursing staff of a general hospital in Qazvin Province, Iran.METHODS: This cross-sectional study was conducted in a general hospital in Qazvin during last 6 months of 2016 and first 6 months of 2017. The target population in the present study was nursing groups based on their highest work experience, from each section in hospital. The SPAR-H method was used to investigate human error in the population and the collected data were analyzed using SPSS software.RESULTS: The highest error related to inappropriate venipuncture with probability of 0.7, and the least probable error related to error in entering the numbers of vital signs with the probability of 0.0045.CONCLUSION: Due to the sensitivity of the role of nurses in hospitals, the need for increased workforce, the use of people with higher work experience in sensitive sectors, reducing overtime even for those who volunteered to work overtime, scientific scheduling of the personnel’s work shifts, and providing practical training such as stress control methods in case of emergencies can be effective in reducing the probability of an error

Dark Web Activity Classification Using Deep Learning

In contemporary times, people rely heavily on the internet and search engines to obtain information, either directly or indirectly. However, the information accessible to users constitutes merely 4% of the overall information present on the internet, which is commonly known as the surface web. The remaining information that eludes search engines is called the deep web. The deep web encompasses deliberately hidden information, such as personal email accounts, social media accounts, online banking accounts, and other confidential data. The deep web contains several critical applications, including databases of universities, banks, and civil records, which are off-limits and illegal to access. The dark web is a subset of the deep web that provides an ideal platform for criminals and smugglers to engage in illicit activities, such as drug trafficking, weapon smuggling, selling stolen bank cards, and money laundering. In this article, we propose a search engine that employs deep learning to detect the titles of activities on the dark web. We focus on five categories of activities, including drug trading, weapon trading, selling stolen bank cards, selling fake IDs, and selling illegal currencies. Our aim is to extract relevant images from websites with a ".onion" extension and identify the titles of websites without images by extracting keywords from the text of the pages. Furthermore, we introduce a dataset of images called Darkoob, which we have gathered and used to evaluate our proposed method. Our experimental results demonstrate that the proposed method achieves an accuracy rate of 94% on the test dataset.Comment: 11 pages , 16 figures , 2 tables , New Dataset For DarkWeb Activity Classificatio

Quality evaluation and stability index determination of Qom rural drinking water resources

Background and Aims: Corrosion and scaling are among the problems that despite science advancement, water facilities are still faced it. Corrosion lead to financial and health losses on water supply system and consumer, scaling also causes clogging and head loss in water supply network. Therefore, the aim of this study is to determine the corrosion and scaling potential of Qom villages water supply sources.Materials and Methods: In cross-sectional study 100 samples in 12 months from 2011 to 2012 were collected to verify the water quality according to 1053 standard of Institute of Standards and Industrial Research of Iran (ISIRI). Then water corrosion and scaling were studied using Langelier, Ryznar, Aggressive and Puckorius indexes.Results: The results showed that the Langelier index, Reynar index, aggressive or corrosion index and index Puckorius were -1.62 (±0.11), 10.5 (±0.17), 12.03 (±0.14) and 9.92 (±0.13) respectively. Physical and chemical parameters of the water showed that the mean pH, TDS, total hardness, turbidity, calcium, magnesium, fluoride, sodium, ammonia, phosphate, and chloride were 7.27, 1205.29 mg/L, 435.661 mg/L CaCO3, 0.747 NTU, 132.29 mg/L, 25.58 mg/L, 0.68 mg/L, 245.50 mg/L, 0.015 mg/L, 0.17 mg/L and 231.22 mg/L respectively.Conclusion: The amounts of color, TDS, turbidity, pH, calcium, magnesium, fluoride and ammonia in the study areas are in satisfactory and acceptable status compared to the internal standard but the amount of phosphate, hardness and chloride in this area were exceeded from permissible limit. Comparison of four stability index also showed that water conditions in all parts of this study are located in corrosive range.Key words: Drinking water, Villages of Qom province, Stability inde

Developing a Robust Surrogate Model of Chemical Flooding Based on the Artificial Neural Network for Enhanced Oil Recovery Implications

Application of chemical flooding in petroleum reservoirs turns into hot topic of the recent researches. Development strategies of the aforementioned technique are more robust and precise when we consider both economical points of view (net present value, NPV) and technical points of view (recovery factor, RF). In current study many attempts have been made to propose predictive model for estimation of efficiency of chemical flooding in oil reservoirs. To gain this end, a couple of swarm intelligence and artificial neural network (ANN) is employed. Also, lucrative and high precise chemical flooding data banks reported in previous attentions are utilized to test and validate proposed intelligent model. According to the mean square error (MSE), correlation coefficient, and average absolute relative deviation, the suggested swarm approach has acceptable reliability, integrity and robustness. Thus, the proposed intelligent model can be considered as an alternative model to predict the efficiency of chemical flooding in oil reservoir when the required experimental data are not available or accessible

Optimization of removal of COD and color from baker’s yeast wastewater by Fenton oxidation

Background and Objectives: Bakery’s yeast industry wastewater contains various pollutants and is generally characterized with high chemical oxygen demand (COD), dark color, high-nitrogen and sulfate and non-biodegradable organic pollutants. Having persistent soluble colored compounds (called melanoidins), effluent from yeast industry is a major source of water and soil pollution. The aim of this study was to evaluate advanced oxidation efficiency using Fenton process for COD and color removal from bakery’s yeast wastewater. Materials and Methods: This was an experimental- laboratory scale study. In this study, the effect of time and Fenton concentrations were tested for COD and color removal from bakery’s yeast wastewater. The sample used for this study was yeast effluent from Separator 2 with initial concentrations of COD and color of 5300 mg/L and 6950 pt-co respectively. In order to obtain the optimum operating conditions of the process, Taguchi analysis method was used. Experiments were carried out in five stages of the time in the range of 15, 30, 45, 60 and 75 min with various concentrations of hydrogen peroxide (e.g., 0.02, 0.04, 0.06, 0.08, and 0.1 molar) and concentrations of Fe2+ (e.g., 0.01, 0.02, 0.03, 0.04, and 0.05 molar) at pH = 3. Jar test method was used to determine the best operating conditions including: reaction time, dosages of hydrogen peroxide and Fe2+. Results: According to Taguchi method and SN-ratio analysis, the best H2O2/Fe2+ dosages were 0.08/0.04 molar at pH 3 and in reaction time of 30 min for removal of COD and color. For these conditions, the maximum COD and color removal efficiencies were 63 and 69 percent respectively. Based on the results, with increasing reaction time, there was no perceptible change in the removal efficiency. Conclusion: It can be concluded that Fenton’s oxidation method can be used successfully, as an alternative option to the design and choice of color and COD removal from strength industrial wastewaters e.g., bakery’s yeast industry

Association between splenectomy and pulmonary hypertension in patients with major beta- thalassemia

Background and purpose: Increased pressure in the pulmonary circulation is of the major factors causing cardiac disorders in patients with thalassemia. The aim of this study was to investigate the relationship between splenectomy and pulmonary arterial pressure in individuals with beta- thalassemia major. Materials and methods: A cross-sectional study was carried out in patients with beta-thalassemia attending Hajar Hospital Shahrekord, Iran, 2015. All patients underwent echocardiography and the hemoglobin levels, platelet count, ferritin, pressure, pulmonary arterial pressure, etc. were measured. Data analysis was done in Stata 13. Results: Among the variables measured, the average age, hemoglobin level, platelet count, nucleated RBC, lactate dehydrogenase, tricuspid regurgitation flow, pulmonary arterial pressure, right diameter, main pulmonary diameter, left ventricular end diastolic diameter, left ventricular end systolic diameter were found to be higher in patients with splenectomy, compared to those of the patients without splenectomy (P> 0.05). Significant correlation was observed between platelets, NRBC and the time of splenectomy with pulmonary artery pressure (P 0.05). Conclusion: The results showed that splenectomy could increase the susceptibility to pulmonary artery pressure in patients with beta thalassemia major or lead to the progression of pulmonary hypertension in this disease

A survey of the relationship between disclosure quality (on time and reliability) and accruals management in the financially distressed companies

The purpose of this research is the investigation of relationship between disclosure quality and accruals management in the financially distressed companies. To operationalize the disclosure quality, disclosure score presented by stock market was used. Adjusted model of Jones (1991) was applied for separation of discretionary and nondiscretionary accruals. Charitou et al. model (2004) was used for measurement of bankruptcy risk and determined the financially distressed companies. 249 firms listed in Tehran Stock Exchange were used as sample study for 2003-2009 to test the hypotheses and determining the relation between disclosure quality and accruals management and Panel Data system was used for analysis. The results show that there is a positively significant association between the accruals management (discretionary accruals) and disclosure quality. Also, the relationship between disclosure quality and accruals management in financially distressed companies had significant difference with the relationship with financially non-distressed companies. The results of the study showed that by the increase of bankruptcy risk, the relation between disclosure quality and accruals management is not weak significantly