New Advances in Membrane Technology

Non

Application of artificial neural network for prediction of halogenated refrigerants vapor pressure

Application of Artificial Neural Network (ANN) for modeling of vapor pressure for some halogenated refrigerants (halogenated methanes and ethanes) is presented. Neural network training structure was feed forward with back-propagation algorithm. The optimized number of hidden layer and neurons between layers were determined by a trial and error procedure. Neural network parameters were obtained through a learning phase by Levenberg-Marquardt algorithm. The vapor pressure at different temperatures obtained from open literatures was considered as the neural model target. ANN predictions of vapor pressure are more accurate for a wider range of temperature. The ANN modeling reduced the average error for the refrigerants from 0.69% to 0.31% for low temperature range and from 1.39% to 0.99% for high temperature range. Finally, ANN modeling reduced the average error in comparison to theAntoine equation by 47.88% and 32.18% for low and high temperature range, respectively

A Business Model to Detect Disease Outbreaks

Introduction: Every year several disease outbreaks, such as influenza-like illnesses (ILI) and other contagious illnesses, impose various costs to public and non-government agencies. Most of these expenses are due to not being ready to handle such disease outbreaks. An appropriate preparation will reduce the expenses. A system that is able to recognize these outbreaks can earn income in two ways: first, selling the predictions to government agencies to equip and make preparations in order to reduce the imposed costs and second, selling predictions to pharmaceutical companies to guide them in producing the required drugs when a disease spreads. This production can specify probable markets to these companies. Methods: Both earning methods would be considered in this modeling and costs and incomes will be discussed according to basic business models (especially in the health field). To execute this model, the internet is used as a recipient of information from the doctors and the service providers for prediction. To ensure collaboration of doctors in the data collection process, the amount of money that is paid is proportional to the rate of sending the patients’ information. On the other hand, customers can access outbreak prediction information about a specific illness after payment or subscription of system for monthly periods. All the money transfered in this system would be via online credit systems. Results: This business model has three main values: recognizing disease outbreaks at the right time, identifying factors and estimating the spreading rate of the disease and, the categorization of customers in this model is based on the value provided including pharmaceutical companies and importers of drugs, the government, insurance companies, universities and research centers. By considering various markets, this model has the ROI of 0.5 which means the investment in it reverses in 6 months. Conclusion: According to the results, the business model developed in this study, has fair value and is feasible and suitable for the web. This model develops medical information network and proper marketing, earns good profits and the most critical resource of it is the algorithm that detects the disease outbreak which must be properly constructed and used

Fecal examination of the equids of Tabriz from the viewpoint of gastrointestinal helminthes infestation

From July to October 2006, fecal samples were collected from 242 horses and ponies of Tabriz jockey clubs and 119 local equids in order to determine their EPG and parasitic fauna of gastrointestinal helminthes. After performing the Clayton- laen method of floatation test using zinc chloride and saturated sodium chloride solutions, it was determined that the feces of 40% of jockey club horses and 78.15% of local equids were infected by the eggs of parasitic gastrointestinal helminthes. Trichuris eggs were observed in 4.2% of the feces of local equids. Fecal culture revealed that all the eggs in the feces of jockey club horses were small strongyles while 2 of the local equids were infected by Strongyles vulgaris and the rest by small strongyles. Based on independent t-test, the differences between males and females and different age groups were insignificant

Concentrating of Sugar Syrup in Bioethanol Production Using Sweeping Gas Membrane Distillation

Membrane distillation (MD) is a relatively new and underdeveloped separation process which can be classified as a green technology. However, in order to investigate its dark points, sensitivity analysis and optimization studies are critical. In this work, a number of MD experiments were performed for concentrating glucose syrup using a sweeping gas membrane distillation (SGMD) process as a critical step in bioethanol production. The experimental design method was the Taguchi orthogonal array (an L9 orthogonal one) methodology. The experimental results showed the effects of various operating variables, including temperature (45, 55, and 65 °C), flow rate (200, 400, and 600 ml/min) and glucose concentration (10, 30, and 50 g/l) of the feed stream, as well as sweeping gas flow rate (4, 10, and 16 standard cubic feet per hour (SCFH)) on the permeate flux. The main effects of the operating variables were reported. An ANOVA analysis showed that the most and the least influenced variables were feed temperature and feed flow rate, each one with 62.1% and 6.1% contributions, respectively. The glucose rejection was measured at 99% for all experiments. Results indicated that the SGMD process could be considered as a versatile and clean process in the sugar concentration step of the bioethanol production

Preparation of Ethylene Vinyl Acetate/Zeolite 4A Mixed Matrix Membrane for CO2/N2 Separation

A great contribution in research activities on carbon dioxide (CO2) separation, as the most important challenge in greenhouse gases control, has been made to develop new polymeric membranes. In this case, mixed matrix membranes (MMMs), comprised of rigid particles dispersed in a continuous polymeric matrix, was proposed as an effective method to improve the separation properties of polymeric membranes. In this research, ethylene vinyl acetate (EVA) copolymer and zeolite 4A powders were applied to prepare MMMs using solution casting/solvent evaporation method and CO2/N2 separation performance of the membranes was examined under different feed pressures (3-8 bar) and operating temperatures (25-50°C). Morphological and structural characterizations of the membranes were evaluated using scanning electron microscopy (SEM), Fourier transform infrared (FTIR) spectroscopy, differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), density and solvent-induced swelling measurements. The gas permeability measurements through the constant-volume method showed the permeability of two gases increased in the presence of zeolite 4A nanoparticles in the polymer matrix. Calculation of diffusivity coefficients of gases revealed that improvement in the diffusivity of all gases into membrane matrix was the main reason for permeability enhancement. In addition, the increase in the CO2/N2 ideal selectivity with the presence of zeolite 4A nanoparticles in the polymer matrix was attributed to the increment in CO2/N2 diffusion selectivity. Under optimum condition, with the addition of 10 wt% zeolite 4A nanoparticles into the membrane matrix, the CO2 permeability increased from 20.81 to 35.24 Barrer and its related selectivity increased 20% compared to that of neat EVA membrane. Furthermore, the membrane performances increased upon feed pressure rise, while the selectivity decreased with the increase in temperature

Preparation and Characterization of a Cross-linked Matrimid/Polyvinylidene Fluoride Composite Membrane for H2/N2 Separation

A double layer composite membrane was fabricated by matrimid 5218 as a selective layer on polyvinylidene fluoride (PVDF), a porous asymmetric membrane, as a sublayer. The effect of chemical cross-linking of Matrimid 5218 by ethylenediamine (EDA) was investigated on gas transport properties of the corresponding membrane. The permeability levels of hydrogen (H2) and nitrogen (N2) were measured through the fabricated composite membranes at 25°C under pressure range of 2-8 bar. Scanning electron microscopy (SEM) was used for morphological observations of the composite membranes. The Matrimid membranes before and after cross-linking modification were characterized by the Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD) and density measurement. The FTIR results showed the conversion of imide functional groups into amide through the crosslinking reaction in Matrimid. The XRD results demonstrated a reduction in d-spacing between the polymer chains through cross-linking reaction. Measuring the density of each membrane's partial selective layer and calculating the corresponding fractional free volume revealed an increase in the density and reduced free volumes in Matrimid through the cross-linking reaction. Moreover, by increasing the EDA concentration, the gas permeability in each membrane decreased significantly for nitrogen compared to hydrogen which could be related to lower gas diffusivity through chain packing due to cross-linking of the polymer. The H2/N2 selectivity at 2 bar increased through the cross-linking modification from 56.5 for the pure Matrimid to 79.4 for the composite membrane containing 12 wt% EDA. The effect of pressure on gas permeability through the composite membranes was investigated and the results found to be in agreement with the behavior of less soluble gases in the glassy polymers. Moreover, the H2/N2 selectivity decreased first at low EDA content (0-4 wt%), before reaching a constant value at 8 wt% EDA and finally increasing by 12 wt% EDA content