Chemical, microbial and sensory changes of silver carp (Hypophthalmichthys molitrix) fish treated with black cumin (Nigella sativa L.) extract during storage at refrigerator

The changes in chemical, microbial and quality sensory of fillets for silver carp fish treated with black cumin extract during refrigerated storage were investigated. The fish were divided into two groups. First group was dipped in black cumin extract with concentration of 1% and received the highest score in sensory evaluation. Then the fishes were wrapped in polyethylene package. The second group, as the control samples, were wrapped in polyethylene package after dipping in distilled water. All treatments were stored at refrigerator temperature (1±4°C). The microbial tests including total viable count, psychrotrophic count and chemical tests including peroxide index, thiobarbituric acid, free fatty acid value and total volatile basic nitrogen, with sensory evaluation, were done at 4°C over a period of 15 days. The results showed that the black cumin extract delayed lipid oxidation and protein analyses significantly in treated fishes. Psycrotrophic bacteria and total viable count of samples being treated with black cumin extract were maintained lower than the proposed acceptable limit (7 log cfu/g). In comparison to the control samples, microbial spoilage significantly decreased in treated samples. Furthermore, according to sensory analysis, the treatment with black cumin extract led to high quality during storage.The findings indicated that black cumin exerts had strong antioxidant and antibacterial impacts on silver carp fish, such that the shelf life of fillets being treated with black cumin were 2.5 times more than that of control samples during storage in refrigerator

Neural networks in geophysical applications

Neural networks are increasingly popular in geophysics. Because they are universal approximators, these tools can approximate any continuous function with an arbitrary precision. Hence, they may yield important contributions to finding solutions to a variety of geophysical applications. However, knowledge of many methods and techniques recently developed to increase the performance and to facilitate the use of neural networks does not seem to be widespread in the geophysical community. Therefore, the power of these tools has not yet been explored to their full extent. In this paper, techniques are described for faster training, better overall performance, i.e., generalization,and the automatic estimation of network size and architecture

Genetic risk factors in patients with deep venous thrombosis, a retrospective case control study on Iranian population

Background: Venous thromboembolism (VTE) could be manifested as deep venous thrombosis (DVT) or pulmonary embolism (PE). DVT is usually the more common manifestation and is usually formation of a thrombus in the deep veins of lower extremities. DVT could occur without known underlying cause (idiopathic thrombosis) which could be a consequence of an inherited underlying risk factor or could be a consequence of provoking events, such as trauma, surgery or acute illness (provoked thrombosis). Our aim in this study was to assess the impact of some previously reported genetic risk factors including, methylenetetrahydrofolate reductase (MTHFR) C677T and A1298C, plasminogen activator inhibitor-1(PAI-1) 4G/5G, prothrombin 20210 and FV Leiden on occurrence of DVT in a population of Iranian patients. Methods: This long-term study was conducted on 182 patients with DVT and also 250 age and sex matched healthy subjects as control group. The diagnosis of DVT was based on patient's history, clinical findings, D-dimer test, and confirmed by Doppler ultrasonography. After confirmation of DVT, both groups were assessed for the five mentioned mutations. The relationship between mutations and predisposition to DVT was calculated by using logistic regression and expressed as an OR with a 95 confidence interval (CI). Results: Our results revealed that FV Leiden (OR 6.7; 95 CI = 2.2 to 20.3; P = 0.001), MTHFR C677T (OR 6.0; 95 CI = 2.2 to 16.4; P < 0.001), MTHFR A1298C (OR 8.3; 95 CI = 4.4 to 15.8; P < 0.001), and PAI-1 4G/5G (OR 3.8; 95 CI = 2.1 to 7.2; P < 0.001) mutations were all significantly associated with an increased risk of DVT. Prothrombin 20210 was found in none of the patients and controls. Conclusion: Our findings suggest that genetic risk factors have a contributory role on occurrence of DVT. © 2015 Hosseini et al

NREL Phase VI wind turbine in the dusty environment

The meteorological conditions markedly affect the energy efficiencies and cost/power rate of the wind turbines. This study numerically investigates the performance of the National Renewable Energy Laboratory (NREL) Phase VI wind turbine, designed to be insusceptible to surface roughness, undergoing either clean or dusty air. First, the numerical approach is validated against the available experimental data for clean air. Following this, the model is developed into a Lagrangian-Eulerian multiphase approach to comprehensively analyze the effects of the dusty air. The dependence of aerodynamic performance on the wind speed (= 5-25 m/s), particle diameter dp (= 0.025-0.9 mm) and angle of attack (= 0o-44o) is investigated. It is found that the turbine performance generally deteriorates in dusty conditions. But it becomes relatively acute for dp > 0.1 mm and post-stall state. As such, the generated power is reduced by 4.3% and 13.3% on average for the air with the dp = 0.05 and 0.9 mm, respectively. The particles change the flow field profoundly, declining the pressure difference between the suction/pressure sides of the blade-airfoil, advancing the boundary layer separation, and strengthening the recirculation zones. The above changes account for a lower lift coefficient and higher drag coefficient