Effect of different heating treatments and kind of filling media on the amounts of some mineral elements (iron, zinc, copper, calcium and sodium) of silver carp (Hypopthalmichthys molitrix) during canning

In this study, first, the influence of three precooking methods (steaming, oven-baking and microwave-cooking) on the contents of mineral elements-copper, zinc, iron, calcium and sodium-of silver carp (Hypophthalmichthys molitrix) was evaluated. Determination results of evaluated elements in raw fish and cooked samples were in range 3.05 to 4.19 for copper, 71.45 to 82.85 for zinc, 32.18 to 40.70 for iron, 425.6 to 529.46 and 315.5 to 534.76 for calcium. Results showed different precooking treatments had no significant effects on the amounts of mineral elements such as copper, zinc, calcium and sodium. The Iron content in the samples subjected to microwave cooking increased. With doing multivariate analysis, on comparing the raw and precooked fillets, steam cooking found to be the best precooking method on retain mineral elements. After choosing the best precooking method, for evaluating the influence of different filling media including sunflower oil, soybean oil, olive oil and brine, on the quality of canned silver carp, amounts of mineral elements(copper, zinc, iron, calcium and sodium) and microbial indices(total counts, thermopile count and clostridium) and sensory indices (color, smell, taste and texture) was surveyed. Assessments of microbial indices showed no microbial activity in canned products. After canning amounts of sodium increased in all the treatments. Except for iron, using soybean oil had no significant effect on the contents of other elements. The highest levels of iron and copper were observed in olive oil canned samples sterilized at 130°C. Sensory evaluating showed, kind of filling media had no significant effects on sensory indices such as taste, smell and color of canned samples. The texture of soybean oil canned samples and the quality defects of olive oil and brine canned samples had better condition than other treatments. In the last step, canned silver carp were proceed under three different temperatures (115°C, 120°C and 130°C) with equal lethality value (Fo=7min), then sensory indices and amount of mineral elements were compared. Results showed, the contents of iron, copper, sodium and calcium were changed in soybean oil canned sample. The amounts of copper and sodium in sunflower oil canned sample subjected to different heating regimes showed significant variation. The highest amount of copper was observed in the canned samples subjected to 130°C heating regime. Results showed contents of iron and copper of olive oil canned sample subjected to 120°C and 130°C heating regimes were higher than sample subjected to 115°C heating regime, while the zinc and calcium contents had no variation. In brine canned samples the highest amounts of copper and iron was obtained after sterilization in 120°C. Results of sensory evaluation showed different heating regimes had no significant effects on the indices of taste, smell, and color of products. Doing 130°C heating regime in brine canned samples led to obtain the better tenacity of texture. While this heating regime caused to increase the quality defects of soybean oil canned samples as a result of existence of hard parts of bone

Global variations in diabetes mellitus based on fasting glucose and haemogloblin A1c

Fasting plasma glucose (FPG) and haemoglobin A1c (HbA1c) are both used to diagnose diabetes, but may identify different people as having diabetes. We used data from 117 population-based studies and quantified, in different world regions, the prevalence of diagnosed diabetes, and whether those who were previously undiagnosed and detected as having diabetes in survey screening had elevated FPG, HbA1c, or both. We developed prediction equations for estimating the probability that a person without previously diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa. The age-standardised proportion of diabetes that was previously undiagnosed, and detected in survey screening, ranged from 30% in the high-income western region to 66% in south Asia. Among those with screen-detected diabetes with either test, the agestandardised proportion who had elevated levels of both FPG and HbA1c was 29-39% across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and middle-income regions, isolated elevated HbA1c more common than isolated elevated FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and underestimate diabetes prevalence. Our prediction equations help allocate finite resources for measuring HbA1c to reduce the global gap in diabetes diagnosis and surveillance.peer-reviewe

Prediction of reservoir brine properties using radial basis function (RBF) neural network

Aquifers, which play a prominent role as an effective tool to recover hydrocarbon from reservoirs, assist the production of hydrocarbon in various ways. In so-called water flooding methods, the pressure of the reservoir is intensified by the injection of water into the formation, increasing the capacity of the reservoir to allow for more hydrocarbon extraction. Some studies have indicated that oil recovery can be increased by modifying the salinity of the injected brine in water flooding methods. Furthermore, various characteristics of brines are required for different calculations used within the petroleum industry. Consequently, it is of great significance to acquire the exact information about PVT properties of brine extracted from reservoirs. The properties of brine that are of great importance are density, enthalpy, and vapor pressure. In this study, radial basis function neural networks assisted with genetic algorithm were utilized to predict the mentioned properties. The root mean squared error of 0.270810, 0.455726, and 1.264687 were obtained for reservoir brine density, enthalpy, and vapor pressure, respectively. The predicted values obtained by the proposed models were in great agreement with experimental values. In addition, a comparison between the proposed model in this study and a previously proposed model revealed the superiority of the proposed GA-RBF model

Molecular characterization of Escherichia coli recovered from traditional milk products in Kashan, Iran

Aim: Shiga toxigenic Escherichia coli (STEC) strains as emerging groups of foodborne pathogens are responsible for most foodborne illnesses. The aim of this study was to determine the antibiotic resistance pattern in STEC isolated from traditional milk products and their molecular characterization. Materials and Methods: A total of 116 samples were randomly purchased from local markets in Kashan, Iran, and evaluated for the occurrence of STEC by culturing and molecular methods. The antibiotic resistance of obtained isolates was determined by Kirby Bauer method. Furthermore, isolates were assayed for the presence of Shiga toxins (stx1 and stx2) and intimin gene (eae). Results: The incidence of E. coli in 60 ice cream, 30 yoghurt, and 26 cheese samples was 8.33%, 10%, and 11.54%, respectively. The findings showed that 11 out of 11 (100%) E. coli had both stx1 and stx2 while eae gene was not found in E. coli isolated of traditional milk products. For E. coli strains carrying stx1 and stx2, highest antibiotic sensitive levels were related to trimethoprim/sulfamethoxazole, norfloxacin, chloramphenicol, and ciprofloxacin, respectively. Conclusion: The results showed relationship between the presence of virulence factors and antimicrobial resistance. These results can be used for further studies on STEC as an emerging foodborne pathogen

Prediction of carbon dioxide solubility in ionic liquids using MLP and radial basis function (RBF) neural networks

Elimination of carbon dioxide from gas mixtures is a common commercial step in natural gas refineries. Nowadays, room-temperature ionic liquids, which are a relatively novel type of compounds have gained attention in recent years and have potential to be considered as a substitution for conventional volatile organic solvents in reaction and separation processes. No flammability, high thermal stability, a wide liquid range, and electric conductivity are some properties of ILs, which make them interesting more and more. Information about the solubility and the rate of solubility is a crucial factor for consideration of ILs for potential industrial processes. Because of some difficulties associated with experimental measurements and expenses spent on ILs, developing predictive methods for prognostication of the phase behavior of such types of systems are more favorable. Thermodynamic models are relatively complex and require complicated mathematical operations. Due to such difficulties there is a need to develop general models capable to predict phase behavior of systems such as CO2 with various kinds of ILs. In this study, four different methods based on artificial intelligence are proposed to predict CO2 solubility in different ionic liquids. The results showed that the predicted values are in great agreement with the experimental data and the maximum absolute error deviation for the best predictor is no more than 3.5%. A comparison between developed models and previously published ones reveals the superiority of the proposed models in this study

Prediction of water formation temperature in natural gas dehydrators using radial basis function (RBF) neural networks

Raw natural gases usually contain water. It is very important to remove the water from these gases through dehydration processes due to economic reasons and safety considerations. One of the most important methods for water removal from these gases is using dehydration units which use Triethylene glycol (TEG). The TEG concentration at which all water is removed and dew point characteristics of mixture are two important parameters, which should be taken into account in TEG dehydration system. Hence, developing a reliable and accurate model to predict the performance of such a system seems to be very important in gas engineering operations. This study highlights the use of intelligent modeling techniques such as Multilayer perceptron (MLP) and Radial Basis Function Neural Network (RBF-ANN) to predict the equilibrium water dew point in a stream of natural gas based on the TEG concentration of stream and contractor temperature. Literature data set used in this study covers temperatures from 10 °C to 80 °C and TEG concentrations from 90.000% to 99.999%. Results showed that both models are accurate in prediction of experimental data and the MLP model gives more accurate predictions compared to RBF model

Modified unilateral periureteral injection technique in the treatment of patients with high-grade vesicoureteral reflux: A study of primary findings

Objective: Although endoscopic treatment has been used by many pediatric urologists for the treatment of vesicoureteral reflux (VUR), it has no considerable success in high-grade VUR. We aimed to describe the primary outcomes of unilateral periureteral injection technique (PIT), as well as bilateral PIT in high-grade VUR. Methods: In this prospective study, we examined 92 ureters in 45 boys and 40 girls from February 2010 to May 2018. Bilateral PIT and unilateral PIT were applied in 67 and 25 refluxing units, respectively. In the unilateral PIT, the subureteral injection site was only at the 5- or 7-o'clock position. However, in the bilateral PIT, the subureteral injection sites were at 5- and 7-o'clock position. Pre- and post-operative reflux grades were evaluated by voiding cystourethrography 6 months after surgery. Results: Seven patients had bilateral reflux. Overall, 75 (81.5%) ureters showed Grade IV VUR, while 17 (18.5%) had primary Grade V VUR. The mean age of the subjects was 39.2 months. In unilateral PIT ureters, VUR was resolved in 23 (92.0%) refluxing units. It was downgraded to Grade III in one ureter (4.0%) and to Grade II in another ureter (4.0%). In addition, in bilateral PIT cases, VUR was resolved in 60 (89.6%) ureters; it downgraded to Grades II and III in 3 (4.5%) and 4 (6.0%) refluxing units, respectively. Conclusion: Unilateral PIT can be highly effective in the treatment of selected ureters of high-grade VUR. However, further studies are needed to confirm our results