Improving urban run-off quality using iron oxide nanoparticles with magnetic field

Run-off from road surfaces is a major source of pollution in the environment. The aim of this study was to investigate the efficiency of nano iron oxide under a magnetic field to improve urban run-off quality. Experiments were conducted in a 50mm diameter column made of Plexiglass in which 20 cm deep stainless steel wool was used as the medium bed. A pair of magnets, each with 0.7 T magnetic charge density, was installed around the column. The particle size of the iron oxide was determined by X-ray diffraction (XRD) analysis. Atomic absorption spectroscopy, spectrophotometer, turbidimeter, and pH meter were used to measure heavy metals, nitrate and phosphate, turbidity and pH, respectively. Results from XRD analysis revealed that the average nanoparticle size was 32 nm. The average removal efficiency for turbidity, Pb, Zn, Cd, and phosphate were 41.5, 93.9, 96.2, 88.4, and 87.4%, respectively. However, nitrate was not removed from the column tests. The results of this study showed that nano iron oxide in the presence of magnetic field has the potential to improve urban run-off quality. However, for further reduction of turbidity and nitrate removal other options should be considered

TWO-EPOCH OPTIMAL DESIGN OF DISPLACEMENT MONITORING NETWORKS

In the traditional method of optimal design of displacement monitoring networks a higher precision, √2 times better than the desired accuracy of displacements, is considered for the net points in such a way that the accuracy of the detected displacements meets the desired one. However, in this paper, we develop an alternative method by considering the total number of observations in two epochs without such a simple assumption and we call it two-epoch optimisation. This method is developed based on the Gauss-Helmert adjustment model and the variances of the observations are estimated instead of the weights to optimise the observation plan. This method can deliver the same results as the traditional one, but with less required observations in each epoch

Adaptive Molecule Transmission Rate for Diffusion Based Molecular Communication

In this paper, a simple memory limited transmitter for molecular communication is proposed, in which information is encoded in the diffusion rate of the molecules. Taking advantage of memory, the proposed transmitter reduces the ISI problem by properly adjusting its diffusion rate. The error probability of the proposed scheme is derived and the result is compared with the lower bound on error probability of the optimum transmitter. It is shown that the performance of introduced transmitter is near optimal (under certain simplifications). Simplicity is the key feature of the presented communication system: the transmitter follows a simple rule, the receiver is a simple threshold decoder and only one type of molecule is used to convey the information

Comparison between conventional pump and adsorption sampling method with passive solid phase microextraction ( SPME ) sampling to investigate changes in the concentration of benzene, toluene , and xylene ( BTX ) in urban ambient air

Background and Aims: Besides toxic effects on human, animals and plants, aromatic hydrocarbons may also be effective in the formation of photochemical smog. The measurement of these hydrocarbons, therefore, play aprominent part in evaluating their health and environmental impacts. The purpose of this study was to compare pump and adsorption sampling method with solid phase microextraction (SPME) to investigate changes in theconcentration of benzene, toluene, and xylene (BTX).Materials and Methods: SPME samplers in sampling protective holders were placed in ambient air at a relatively high traffic routes for 5 days. Sampling was carried out in two seasons. Samples were analyzed at the end of sampling period. In addition, pump and adsorption sampling method was also used to measure the concentrations of benzene, toluene, and xylene. Ethical issues were all considered in conducting the study and citation.Results: The obtained results in solid phase microextraction sampling method were compared with those obtained using the conventional pump and adsorbent method. Correlation coefficients (R2) between these methods were 0.98, 0.9 and 0.95 for benzene, toluene, and xylene, respectively. The results obtained with pump and adsorption method showed a higher values in general.Conclusion: The comparison between obtained results with these methods indicates a relatively similar values. It may be concluded that SPME sampling method can also present reliable results for the measurement of benzene,toluene and xylene concentrations in the ambient air.Keywords: Passive sampling, SPME, Benzene, Toluene, XyleneFor downloading the full text please click here

Biological hydrogen production from synthetic wastewater by an anaerobic migrating blanket reactor: Artificial neural network (ANN) modeling

Background: This study aimed to evaluate an anaerobic migrating blanket reactor (AMBR) for biological hydrogen production, and also to investigate its capability to treat synthetic wastewater. Methods: A five-compartment AMBR (9 L effective volume) was made by Plexiglas and seeded with thermal pretreated anaerobic sludge at 100°C for 30 minutes. The AMBR was operated at mesophilic temperature (37 ± 1°C) with continuous fed of synthetic wastewater at five organic loading rates (OLRs) of 0.5 to 8 g COD/L.d. Results: It was revealed that as the OLR increased from 0.5 to 8 g COD/L.d, the hydrogen production and also volumetric hydrogen production rate (VHPR) improved. Increasing the OLR over this range, led to a decrease in the average hydrogen yield from 1.58 ± 0.34 to 0.97 ± 0.45 mol H2/mol glucose. The concentration of both volatile fatty acids (VFAs) and solvents kept increasing with OLR. During the AMBR operation, the dominant soluble end products (SEPs) were acetic and butyric acids in all of the OLRs studied. Conclusion: Based on the results, the hydrogen yield was related to the acetate/butyrate fermentation. The artificial neural network (ANN) model was well-fitted to the experimental obtained data from the AMBR, and was able to simulate the chemical oxygen demand (COD) removal and hydrogen production. Keywords: AMB reactor, Fatty acids, Fermentation, Hydrogen, Wastewater treatmen

Evaluating the performance of clarification and ultraviolet units in disinfection of Isfahan North waste water treatment plant (WWTP) effluent in pilot plant

زمینه و هدف: استفاده از پساب تصفیه خانه فاضلاب شهری به خصوص در مصارف کشاورزی مستلزم گندزدایی پساب تا حد استاندارد می باشد. کاربرد اشعه UV به دلیل معایب کمتر در مقایسه با سایر گندزداها، در نقاط مختلف دنیا در حال گسترش است. هدف از انجام این مطالعه بررسی امکان تصفیه و گندزدایی پساب تصفیه خانه فاضلاب شمال اصفهان با واحد زلال سازی و اشعه UV می باشد. روش بررسی: در این مطالعه تجربی از یک واحد زلال ساز و دو نوع سیستم گندزدایی فرابنفش کم فشار (LP) و فشار متوسط (MP) جهت گندزدایی پساب ثانویه استفاده شد. پارامترهای میکروبی کلیفرم کل و مدفوعی، استرپتوکوک مدفوعی و همچنین پارامترهای شیمیایی کل مواد معلق TSS (Total Suspended Solids)، آهن، سختی، جذب و عبور اشعه UV در نمونه های برداشت شده قبل و بعد از واحدها مورد آزمایش قرار گرفت. داده ها با استفاده از آزمون آماری t زوجی تجزیه و تحلیل گردید. یافته ها: متوسط عبور اشعهUV در طول موج nm254 (نانومتر) از پساب زلال شده 34 درصد و میزان جذب اشعهau/cm 47/0 بدست آمد. در گندزدایی پساب زلال شده توسط لامپ LP، MP و تلفیق هر دو نوع لامپ، به ترتیب در دوز اشعه 400، 576 و mws/cm2 407 (میلی وات ثانیه بر سانتی متر مربع) غلظت کلیفرم‌ها به حد استاندارد سازمان حفاظت محیط زیست ایرانml) 100 FC/ 400 و TC1000 (رسید و تعداد استرپتوکوک مدفوعی در دوزهای mws/cm2400، 422 و mws/cm2407 تا log 5 کاهش یافت (05/0

A survey of factors related to urine iodine levels in elementary school children, Kurdistan, Iran

BACKGROUND: Iodine deficiency disorders (IDD) control program has two important factors: annual monitoring of urine iodine levels and controlling iodized salt consumed in the community. Preserving the iodine indexes in different level is important now too. This survey determined factors affecting median levels of urine iodine levels in students of Kurdistan Province (Iran). METHODS: This cross-sectional study selected 255 8-10-year-old students using cluster random sampling. Data was obtained by a questionnaire and urine analysis. The collected data was analyzed by Mann-Whitney and Kruskal-Wallis tests, Spearman correlation, and multiple regression. All analyses were performed using SPSS. RESULTS: The median urine iodine level of the studied school children was 9.7 μg/dl. There was no significant relation between urine iodine level and sex, place of residence (rural/urban areas), and household iodized salt intake (r = 0.188, P = 0.003). Overall, 119 families (46.7%) did not appropriately protect their iodized salt. The amount of iodine in salt and the condition in which salt is kept had relationships with children’s urine iodine levels. CONCLUSION: Low median level of urine iodine in students, low household iodized salt, and high use of salt with lesser iodine than the standard value showed that the IDD program in Kurdistan Province has not been successful. Therefore, there is a risk for increased prevalence of Goiter in the region. We recommend interventional programs to improve the current status in the province. KEYWORDS: Goiter, Urine Iodine, Ira

UNSUPERVISED DYNAMIC TOPIC MODEL FOR EXTRACTING ADVERSE DRUG REACTION FROM HEALTH FORUMS

The relationship between drug and its side effects has been outlined in two websites: Sider and WebMD. The aim of this study was to find the association between drug and its side effects. We compared the reports of typical users of a web site called: "Ask a patient" website with reported drug side effects in reference sites such as Sider and WebMD. In addition, the typical users' comments on highly-commented drugs (Neurotic drugs, Anti-Pregnancy drugs and Gastrointestinal drugs) were analyzed, using deep learning method. To this end, typical users' comments on drugs' side effects, during last decades, were collected from the website “Ask a patient”. Then, the data on drugs were classified based on deep learning model (HAN) and the drugs' side effect. And the main topics of side effects for each group of drugs were identified and reported, through Sider and WebMD websites. Our model demonstrates its ability to accurately describe and label side effects in a temporal text corpus by a deep learning classifier which is shown to be an effective method to precisely discover the association between drugs and their side effects. Moreover, this model has the capability to immediately locate information in reference sites to recognize the side effect of new drugs, applicable for drug companies. This study suggests that the sensitivity of internet users and the diverse scientific findings are for the benefit of dis¬tinct detection of adverse effects of drugs, and deep learning would facilitate it